A Low Complexity UWB Localization Algorithm Using Finite-Resolution Quantization

Impulse radio ultra wideband (IR-UWB) technique has attracted interest in indoor localization thanks to its sub-nanosecond (ns) narrow pulse feature offering high timing resolution. However, measuring these short pulses demands high performance analog-to-digital converter (ADC), i.e. 4 giga Hz 8-bit ADC, which is hard to implement in real systems. In this paper, a finite-resolution (FR) quantization based localization method is proposed, revealing that high performance ADCs can be replaced with high speed comparators since a 2-bit quantization is good enough. At first we approximate the post-quantization signal as Gaussian distributed using Bussgang theorem, facilitating the following derivation. Then, practical TOA estimation and iterative Taylor-series (TS) localization algorithm are derived. Subsequently the analytical expressions of Cramer-Rao lower bound (CRLB) of proposed scheme is obtained, theoretically quantifying the performance loss caused by FR quantization. Finally, compared with the full-resolution and signal-strength (SS) approaches via simulation, we prove that our finite-resolution algorithm achieves almost the same performance as traditional full-resolution scheme while dramatically decreasing the complexity.

[1]  Jun Chen,et al.  A Hybrid Framework for Radio Localization in Broadband Wireless Systems , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[2]  Umberto Mengali,et al.  TOA Estimation with the IEEE 802.15.4a Standard , 2010, IEEE Transactions on Wireless Communications.

[3]  WADE FOY,et al.  Position-Location Solutions by Taylor-Series Estimation , 1976, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Bernard Uguen,et al.  Hybrid Data Fusion techniques for localization in UWB networks , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[5]  Hisashi Kobayashi,et al.  Analysis of wireless geolocation in a non-line-of-sight environment , 2006, IEEE Transactions on Wireless Communications.

[6]  Moe Z. Win,et al.  Fundamental Limits of Wideband Localization— Part I: A General Framework , 2010, IEEE Transactions on Information Theory.

[7]  H. Rowe Memoryless nonlinearities with Gaussian inputs: Elementary results , 1982, The Bell System Technical Journal.

[8]  I. Guvenc,et al.  TOA estimation for IR-UWB systems with different transceiver types , 2006, IEEE Transactions on Microwave Theory and Techniques.

[9]  A. Molisch,et al.  IEEE 802.15.4a channel model-final report , 2004 .

[10]  Huarui Yin,et al.  Finite-Resolution Digital Receiver for UWB TOA Estimation , 2012, IEEE Communications Letters.

[11]  Huarui Yin,et al.  Low Complexity Tri-Level Sampling Receiver Design for UWB Time-of-Arrival Estimation , 2011, 2011 IEEE International Conference on Communications (ICC).

[12]  K. C. Ho,et al.  A simple and efficient estimator for hyperbolic location , 1994, IEEE Trans. Signal Process..

[13]  Feng Zheng,et al.  A Hybrid SS–ToA Wireless NLoS Geolocation Based on Path Attenuation: ToA Estimation and CRB for Mobile Position Estimation , 2009, IEEE Transactions on Vehicular Technology.

[14]  G.B. Giannakis,et al.  Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks , 2005, IEEE Signal Processing Magazine.

[15]  Hisashi Kobayashi,et al.  On time-of-arrival positioning in a multipath environment , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[16]  Moe Z. Win,et al.  Fundamental Limits of Wideband Localization— Part II: Cooperative Networks , 2010, IEEE Transactions on Information Theory.

[17]  Davide Dardari,et al.  A theoretical characterization of nonlinear distortion effects in OFDM systems , 2000, IEEE Trans. Commun..