Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffic alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identification, mitigation, and localization techniques have been proposed. This research investigates NLOS identification for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identification. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identification is investigated. Considering narrowband multiple antenna wireless systems, two xv NLOS identification techniques are proposed. Here, the implementation of spatial correlation of channel coefficients across antenna elements as a metric for NLOS identification is proposed. In order to obtain the spatial correlation, a newmulti-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identification technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which useMIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identification in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identification measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identification performance compared to those that only use space, time or frequency.

[1]  Heung-Ryeol You,et al.  The NLOS mitigation technique for position location using IS-95 CDMA networks , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[2]  W. T. Welford,et al.  Optical estimation of statistics of surface roughness from light scattering measurements , 1977 .

[3]  Andreas F. Molisch,et al.  The double-directional radio channel , 2001 .

[4]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[5]  Li Xiong,et al.  A selective model to suppress NLOS signals in angle-of-arrival (AOA) location estimation , 1998, Ninth IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (Cat. No.98TH8361).

[6]  Xenofon D. Koutsoukos,et al.  A Survey on Localization for Mobile Wireless Sensor Networks , 2009, MELT.

[7]  Larry J. Greenstein,et al.  Ricean $K$-Factors in Narrow-Band Fixed Wireless Channels: Theory, Experiments, and Statistical Models , 2009, IEEE Transactions on Vehicular Technology.

[8]  Preben E. Mogensen,et al.  A stochastic MIMO radio channel model with experimental validation , 2002, IEEE J. Sel. Areas Commun..

[9]  Theodore S. Rappaport,et al.  Overview of spatial channel models for antenna array communication systems , 1998, IEEE Wirel. Commun..

[10]  Zhonghai Wang,et al.  Non-line-of-sight identification via phase difference statistics across two-antenna elements , 2011, IET Commun..

[11]  Larry J. Greenstein,et al.  Moment-method estimation of the Ricean K-factor , 1999, IEEE Communications Letters.

[12]  Tomonari Furukawa,et al.  A Time-of-Arrival-Based Positioning Technique With Non-Line-of-Sight Mitigation Using Low-Frequency Sound , 2008, Adv. Robotics.

[13]  Chunjie Duan,et al.  NLOS channel identification and mitigation in Ultra Wideband ToA-based Wireless Sensor Networks , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[14]  Rodney A. Kennedy,et al.  MIMO Channel Correlation in General Scattering Environments , 2006, 2006 Australian Communications Theory Workshop.

[15]  E. Bonek,et al.  What makes a good MIMO channel model? , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[16]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[17]  Chia-Chin Chong,et al.  A Comprehensive Standardized Model for Ultrawideband Propagation Channels , 2006, IEEE Transactions on Antennas and Propagation.

[18]  D. Harmer,et al.  UltraWideBand indoor positioning systems and their use in emergencies , 2004, PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556).

[19]  Pak-Chung Ching,et al.  Time-of-arrival based localization under NLOS conditions , 2006, IEEE Transactions on Vehicular Technology.

[20]  Candice King,et al.  Fundamentals of wireless communications , 2013, 2013 IEEE Rural Electric Power Conference (REPC).

[21]  Ali Abdi,et al.  A new simple model for land mobile satellite channels: first- and second-order statistics , 2003, IEEE Trans. Wirel. Commun..

[22]  Genevieve Baudoin,et al.  A new low complexity NLOS identification approach based on UWB energy detection , 2009, 2009 IEEE Radio and Wireless Symposium.

[23]  Jeffrey H. Reed,et al.  Angle and time of arrival statistics for circular and elliptical scattering models , 1999, IEEE J. Sel. Areas Commun..

[24]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .

[25]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[26]  Chen-Nee Chuah,et al.  Capacity scaling in MIMO Wireless systems under correlated fading , 2002, IEEE Trans. Inf. Theory.

[27]  Antonio Ruiz,et al.  Frequency domain data transmission using reduced computational complexity algorithms , 1980, ICASSP.

[28]  Mohammad Hossein Kahaei,et al.  Improving source localization in LOS and NLOS multipath environments for UWB signals , 2009, 2009 14th International CSI Computer Conference.

[29]  R. CalderbankA.,et al.  Space-time codes for high data rate wireless communication , 2006 .

[30]  Eiji Okamoto,et al.  An anonymous on-demand position-based routing in mobile ad hoc networks , 2006, International Symposium on Applications and the Internet (SAINT'06).

[31]  Lorenzo Mucchi,et al.  A new parameter for UWB indoor channel profile identification , 2009, IEEE Transactions on Wireless Communications.

[32]  H.V. Poor,et al.  Nonparametric nonline-of-sight identification , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[33]  Gaetano Giunta,et al.  Dynamic LOS/NLOS Statistical Discrimination of Wireless Mobile Channels , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[34]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[35]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[36]  Lars Thiele,et al.  Statistics of the Ricean K-Factor at 5.2 Ghz in an Urban Macro-Cell Scenario , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[37]  W. D. Jones,et al.  Keeping cars from crashing , 2001 .

[38]  Moe Z. Win,et al.  Time of Arrival Estimation for UWB Localizers in Realistic Environments , 2006, EURASIP J. Adv. Signal Process..

[39]  Hüseyin Arslan,et al.  Identification of LOS in Time-Varying, Frequency Selective Radio Channels , 2008, EURASIP J. Wirel. Commun. Netw..

[40]  Joseph M. Kahn,et al.  Fading correlation and its effect on the capacity of multielement antenna systems , 2000, IEEE Trans. Commun..

[41]  Reinaldo A. Valenzuela,et al.  V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channel , 1998, 1998 URSI International Symposium on Signals, Systems, and Electronics. Conference Proceedings (Cat. No.98EX167).

[42]  Bernard H. Fleury,et al.  First- and second-order characterization of direction dispersion and space selectivity in the radio channel , 2000, IEEE Trans. Inf. Theory.

[43]  Luc Martens,et al.  Extensive Penetration Loss Measurements and Models for Different Building Types for DVB-H in the UHF Band , 2009, IEEE Transactions on Broadcasting.

[44]  A. Robert Calderbank,et al.  Space-Time Codes for High Data Rate Wireless Communications : Performance criterion and Code Construction , 1998, IEEE Trans. Inf. Theory.

[45]  Kyandoghere Kyamakya,et al.  NLOS detection algorithms for Ultra-Wideband localization , 2007, 2007 4th Workshop on Positioning, Navigation and Communication.

[46]  Matt Welsh,et al.  MoteTrack: A Robust, Decentralized Approach to RF-Based Location Tracking , 2005, LoCA.

[47]  N.B. Mandayam,et al.  Decision theoretic framework for NLOS identification , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).

[48]  T. Purusothaman,et al.  GLS with secure routing in ad-hoc networks , 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

[49]  Ridha Hamila,et al.  Extended Kalman Filter Channel Estimation for Line-of-Sight Detection in WCDMA Mobile Positioning , 2003, EURASIP J. Adv. Signal Process..

[50]  Y. Jay Guo,et al.  Statistical NLOS Identification Based on AOA, TOA, and Signal Strength , 2009, IEEE Transactions on Vehicular Technology.

[51]  Fambirai Takawira,et al.  Spatially and temporally correlated MIMO channels: modeling and capacity analysis , 2004, IEEE Transactions on Vehicular Technology.

[52]  Seyed Alireza Zekavat,et al.  On the Suitable Environments of the Kronecker Product Form in MIMO Channel Modeling , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[53]  Ali Abdi,et al.  A space-time correlation model for multielement antenna systems in mobile fading channels , 2002, IEEE J. Sel. Areas Commun..

[54]  R. M. Buehrer,et al.  Non-line-of-sight identification in ultra-wideband systems based on received signal statistics , 2007 .

[55]  K. Amouris,et al.  Position-based broadcast TDMA scheduling for mobile ad-hoc networks (MANETs) with advantaged nodes , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

[56]  S. Al-Jazzar,et al.  New algorithms for NLOS Identification , 2005 .

[57]  Fernando Seco,et al.  A survey of mathematical methods for indoor localization , 2009, 2009 IEEE International Symposium on Intelligent Signal Processing.

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

[59]  Jiping Li,et al.  Non-parametric Non-line-of-Sight Identification and Estimation for Wireless Location , 2012, 2012 International Conference on Computer Science and Service System.

[60]  Kaveh Pahlavan,et al.  UDP identification and error mitigation in toa-based indoor localization systems using neural network architecture , 2009, IEEE Transactions on Wireless Communications.

[61]  Chia-Chin Chong,et al.  NLOS Identification and Weighted Least-Squares Localization for UWB Systems Using Multipath Channel Statistics , 2008, EURASIP J. Adv. Signal Process..

[62]  P. Beckmann,et al.  The scattering of electromagnetic waves from rough surfaces , 1963 .

[63]  Hüseyin Arslan,et al.  Identification of LOS and NLOS for wireless Transmission , 2006, 2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[64]  Seyed Alireza Zekavat,et al.  Spatially correlated MIMO channel-generation via virtual channel representation , 2006, IEEE Communications Letters.

[65]  Seyed Alireza Zekavat,et al.  High performance non-line-of-sight identification using MIMO-OFDM space frequency correlation statistics , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[66]  Akbar M. Sayeed,et al.  Deconstructing multiantenna fading channels , 2002, IEEE Trans. Signal Process..

[67]  Lassi Hentila,et al.  WINNER II Channel Models , 2009 .

[68]  Weihua Zhuang,et al.  Nonline-of-sight error mitigation in mobile location , 2004, IEEE INFOCOM 2004.

[69]  Seung-Hyun Kong.  TOA and AOD statistics for down link Gaussian scatterer distribution model , 2009, IEEE Transactions on Wireless Communications.

[70]  Theodore S. Rappaport,et al.  A geometrically based model for line-of-sight multipath radio channels , 1996, Proceedings of Vehicular Technology Conference - VTC.

[71]  J. Holtzman,et al.  The non-line of sight problem in mobile location estimation , 1996, Proceedings of ICUPC - 5th International Conference on Universal Personal Communications.

[72]  Pi-Chun Chen,et al.  A non-line-of-sight error mitigation algorithm in location estimation , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[73]  Ernst Bonek,et al.  A stochastic MIMO channel model with joint correlation of both link ends , 2006, IEEE Transactions on Wireless Communications.

[74]  Moe Z. Win,et al.  Nonparametric Obstruction Detection for UWB Localization , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[75]  Weihua Zhuang,et al.  Nonline-of-sight error mitigation in mobile location , 2005, IEEE Trans. Wirel. Commun..

[76]  Saipradeep Venkatraman,et al.  Location using LOS range estimation in NLOS environments , 2002, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367).

[77]  H. Gregory.  A Comprehensive Standardized Model for Ultrawideband Propagation Channels , 2009 .

[78]  Kaveh Pahlavan,et al.  Blockage Identification in Indoor UWB Ranging Using Multi Band OFDM Signals , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[79]  Daniel R. Fuhrmann,et al.  Covariance structures for multidimensional data , 1993, Multidimens. Syst. Signal Process..