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M T ASTER'S HESIS Biological versus Subspace Methods in Sound Localization by Saurabh Dadu Advisor: Prof. P. S. Krishnaprasad CDCSS MS 2001-1 (ISR MS 2001-3) + CENTER FOR DYNAMICS C D - AND CONTROL OF S SMART STRUCTURES The Center for Dynamics and Control of Smart Structures (CDCSS) is a joint Harvard University, Boston University, University of Maryland center, supported by the Army Research Office under the ODDR&E MURI97 Program Grant No. DAAG55-97-1-0114 (through Harvard University). This document is a technical report in the CDCSS series originating at the University of Maryland. Web site http://www.isr.umd.edu/CDCSS/cdcss.html Report Documentation Page Form Approved OMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 3. DATES COVERED 2001 2. REPORT TYPE - 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Biological versus Subspace Methods in Sound Localization 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION Army Research Office,PO Box 12211,Research Triangle Park,NC,27709 REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT see report 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER 19a. NAME OF ABSTRACT OF PAGES RESPONSIBLE PERSON a. REPORT b. ABSTRACT c. THIS PAGE 84 unclassified unclassified unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 ABSTRACT Title of Thesis: BIOLOGICAL VERSUS SUBSPACE METHODS IN SOUND LOCALIZATION Saurabh Dadu, Master of Science, 2001 Thesis directed by: Professor P. S. Krishnaprasad Department of Electrical and Computer Engineering Sound localization is determining the location of sound sources using the mea- surements of the signals received by an array of sensors. Humans and animals possess the natural ability of localizing sound. Researchers have tried to model nature’s way of solving this problem and have come up with di(cid:11)erent methods based on various neuro-physiological studies. Such methods are called biological methods. On the other hand, there is another community of researchers who has looked at this problem from pure signal processing point of view. Among the more popular methods for solving this problem using signal processing techniques are the subspace methods. In this thesis, a comparative study is done between biological methods and subspace methods. Further, an attempt has been made to incorporate the notion of head-related transfer function in the modeling of subspace methods. The implementation of a biological localization algorithm on a DSP board is also presented. BIOLOGICAL VERSUS SUBSPACE METHODS IN SOUND LOCALIZATION by Saurabh Dadu Thesis submitted to the Faculty of the Graduate School of the University of Maryland, College Park in partial ful(cid:12)llment of the requirements for the degree of Master of Science 2001 Advisory Committee: Professor P. S. Krishnaprasad, Chairman Professor Shihab A. Shamma Professor K. J. R. Liu (cid:13)c Copyright by Saurabh Dadu 2001 DEDICATION To my parents ii ACKNOWLEDGEMENTS I wish to express my gratitude for Prof. P. S. Krishnaprasad for his guidance, inspiration and patience over the course of this project work. My interaction with him has helped me develop scienti(cid:12)c thinking and an objective approach to engineering problems. Special thanks to Cli(cid:11) Knoll for his e(cid:11)orts in helping me withtheDSPimplementation. Thetoolswritten byhimmademylifeconsiderably easier. Thanks go to Prof. K. J. R. Liu and Dr. Ram Venkataraman for their useful suggestions. I express my appreciation towards Dr. Didier Depireux, Dr. Elena Grassi, and Mr. Dan Rapczynski for helping me understand the biological methods for sound localization. I would also like to thank my friends Yu Mao, Fumin Zhang and Sean Andersson for their support and help in di(cid:11)erent phases of the implementation. The research was supported in part by the National Science Foundation Learn- ing and Intelligent Systems Iniative Grant CMS9720334, by the O(cid:14)ce of Naval Research under the ODDR&E MURI97 Program Grant No. N000149710501EE to the Center for Auditory and Acoustics Research and by the Army Research O(cid:14)ce under the ODDRE&E MURI97 Program Grant No. DAAG55-97-1-0114 to the Center for Dynamics and Control of Smart Structures (through Harvard University). iii TABLE OF CONTENTS List of Tables vi List of Figures vii 1 Introduction 1 1.1 Sound localization in Biology . . . . . . . . . . . . . . . . . . . . . 1 1.2 Sound localization: a signal processing view . . . . . . . . . . . . . 3 2 Implementation Setup 8 2.1 Hardware Components . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.1 The Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.2 The Coreco Board . . . . . . . . . . . . . . . . . . . . . . . 10 2.1.3 The Host Computer . . . . . . . . . . . . . . . . . . . . . . 10 2.2 Software Components . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2.1 C60 Host API . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.2 C60 Native API . . . . . . . . . . . . . . . . . . . . . . . . . 12 3 Biological Methods for Sound Localization 14 3.1 The Cochlear Model . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1.1 The Cochlea Filter Bank . . . . . . . . . . . . . . . . . . . . 15 3.1.2 Automatic Gain Controller . . . . . . . . . . . . . . . . . . . 17 3.2 Interaural Transfer Function . . . . . . . . . . . . . . . . . . . . . . 21 3.2.1 Binaural Cues . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2.2 Head-Related Transfer Function . . . . . . . . . . . . . . . . 22 3.3 The Localization System . . . . . . . . . . . . . . . . . . . . . . . . 24 3.3.1 Learning of Interaural Transfer Function . . . . . . . . . . . 26 3.3.2 Estimation of direction . . . . . . . . . . . . . . . . . . . . . 28 3.4 Implementation in Real-Time . . . . . . . . . . . . . . . . . . . . . 29 3.5 The Stereausis Algorithm . . . . . . . . . . . . . . . . . . . . . . . 31 4 Subspace Methods 40 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2 The Data Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 iv 4.2.1 The Narrowband Model . . . . . . . . . . . . . . . . . . . . 41 4.2.2 The Wide-band Model . . . . . . . . . . . . . . . . . . . . . 44 4.3 MUSIC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.3.1 Signal and Noise Subspaces . . . . . . . . . . . . . . . . . . 48 4.3.2 Direction-of-Arrival Estimation . . . . . . . . . . . . . . . . 48 4.4 ESPRIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.4.1 Direction-of-Arrival Estimation . . . . . . . . . . . . . . . . 55 4.5 Tracking of moving source . . . . . . . . . . . . . . . . . . . . . . . 57 5 Results and Discussion 60 5.1 Experimental results for KEMAR . . . . . . . . . . . . . . . . . . . 61 5.2 Experimental results for Scout robot . . . . . . . . . . . . . . . . . 61 5.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Bibliography 63 v LIST OF TABLES 3.1 Paramaters of Automatic Gain Controller . . . . . . . . . . . . . . 19 vi