Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Autonomous Positioning Techniques Based on ´ Cramer-Rao Lower Bound Analysis | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 93043 Pages 1-10 DOI ASP 2006 93043 Autonomous Positioning Techniques Based on Cramer-Rao Lower Bound Analysis Mats Rydstrom 1 Andreu Urruela 2 Erik G. Strom 1 and Arne Svensson1 1 Department of Signals and Systems Chalmers University of Technology SE-412 96 Goteborg Sweden 2 Department of Signal Theory and Communications Universitat Politecnica de Catalunya 08034 Barcelona Spain Received 31 May 2005 Revised 6 October 2005 Accepted 11 October 2005 We consider the problem of autonomously locating a number of asynchronous sensor nodes in a wireless network. A strong focus lies on reducing the processing resources needed to solve the relative positioning problem an issue of great interest in resource-constrained wireless sensor networks. In the first part of the paper based on a well-known derivation of the Cramer-Rao lower bound for the asynchronous sensor positioning problem we are able to construct optimal preprocessing methods for sensor clock-offset cancellation. A cancellation of unknown clock-offsets from the asynchronous positioning problem reduces processing requirements and under certain reasonable assumptions allows for statistically efficient distributed positioning algorithms. Cramer-Rao lower bound theory may also be used for estimating the performance of a positioning algorithm. In the second part of this paper we exploit this property in developing a distributed algorithm where the global positioning problem is solved sub-optimally using a divide-and-conquer approach of low complexity. The performance of this suboptimal algorithm is evaluated through computer simulation and compared to previously published algorithms. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION Large-scale wireless sensor networks WSNs have been proposed for a multitude of applications ranging from passive information gathered in remote and