Elsevier

Digital Signal Processing

Volume 23, Issue 1, January 2013, Pages 340-354
Digital Signal Processing

Compressive sensing based sub-mm accuracy UWB positioning systems: A space–time approach

https://doi.org/10.1016/j.dsp.2012.07.012Get rights and content

Abstract

A key challenge to achieve very high positioning accuracy (such as sub-mm accuracy) in Ultra-Wideband (UWB) positioning systems is how to obtain ultra-high resolution UWB echo pulses, which requires ADCs with a prohibitively high sampling rate. The theory of Compressed Sensing (CS) has been applied to UWB systems to acquire UWB pulses below the Nyquist sampling rate. This paper proposes a front-end optimized scheme for the CS-based UWB positioning system. A Space–Time Bayesian Compressed Sensing (STBCS) algorithm is developed for joint signal reconstruction by transferring mutual a priori information, which can dramatically decrease ADC sampling rate and improve noise tolerance. Moreover, the STBCS and time difference of arrival (TDOA) algorithms are integrated in a pipelined mode for fast tracking of the target through an incremental optimization method. Simulation results show the proposed STBCS algorithm can significantly reduce the number of measurements and has better noise tolerance than the traditional BCS, OMP, and multi-task BCS (MBCS) algorithms. The sub-mm accurate CS-based UWB positioning system using the proposed STBCS–TDOA algorithm requires only 15% of the original sampling rate compared with the UWB positioning system using a sequential sampling method.

Section snippets

Depeng Yang received the B.S. and M.S. degrees in electronic engineering from Huazhong University of Science and Technology, Wuhan, China, in 2003 and 2006, respectively. He received the Ph.D. degree in electrical engineering at the University of Tennessee, Knoxville, in 2011. His research interests include compressed sensing, statistical signal processing, cognitive radio and UWB systems. He has authored/coauthored more than 30 journal/conference papers. He was the recipient of 2011 University

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    Depeng Yang received the B.S. and M.S. degrees in electronic engineering from Huazhong University of Science and Technology, Wuhan, China, in 2003 and 2006, respectively. He received the Ph.D. degree in electrical engineering at the University of Tennessee, Knoxville, in 2011. His research interests include compressed sensing, statistical signal processing, cognitive radio and UWB systems. He has authored/coauthored more than 30 journal/conference papers. He was the recipient of 2011 University of Tennessee Chancellors Citation for Extraordinary Professional Promise. He served as the session chair for CISS 2011 and RWS 2011. He also served as the reviewer of IEEE/EURASIP signal processing transaction/Journal and international conferences.

    Husheng Li received the B.S. and M.S. degrees in electronic engineering from Tsinghua University, Beijing, China, in 1998 and 2000, respectively, and the Ph.D. degree in electrical engineering from Princeton University, Princeton, NJ, in 2005. From 2005 to 2007, he worked as a senior engineer at Qualcomm Inc., San Diego, CA. In 2007, he joined the EECS department of the University of Tennessee, Knoxville, TN, as an assistant professor. His research is mainly focused on wireless communications and smart grid. Dr. Li is the recipient of the Best Paper Award of the EURASIP Journal of Wireless Communications and Networks, 2005 (together with his Ph.D. advisor: Prof. H.V. Poor), the best demo award of Globecom 2010 and the Best Paper Award of ICC 2011.

    Zhenghao Zhang received his B.S. degree and Ph.D. degree in Telecommunication engineering from Xidian University, in 2005 and 2011, respectively. Currently, he is a Post doctoral researcher at University of Tennessee. In 2009, he received national scholarship (CSC) to continue his Ph.D. research in University of Tennessee. His research interests include Wide-band Cognitive Radio, Compressed Sensing, and Random Field theory applications.

    Zhenghao Zhang is a reviewer of EURASIP Journal of Wireless Communications and Networks, IET Electronic Letters, and Journal of Wireless Communications and Mobile Computing.

    Gregory D. Peterson received the B.S., M.S., and D.Sc. degrees in electrical engineering and the B.S. and M.S. degrees in computer science from Washington University, St. Louis. He is a professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, Tennessee. He worked at the Air Force Research Lab for four years, where he received the Research and Development Award recognizing him as the best research and design engineer in USAF for 1998. His research interests include parallel processing, electronic design automation, performance evaluation, and high performance reconfigurable computing. He is a member of the ACM and a senior member of the IEEE and the IEEE Computer Society.

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