Localization in sensor networks based on log range observations

This contribution presents a unified framework for localization and tracking in sensor networks based on fusing a variety of signal energy measurements as provided by for instance acoustic, seismic, magnetic, radio, microwave and infrared sensors. The received energy from such sensors generally decays exponentially, and a log range model is introduced for the sensor observations in logarithmic scale, which is linear in transmitted power and the path loss exponent. Field trial sensor data confirms the validity of the log range model. The novelty in this contribution lies in a systematic least squares approach to eliminate these nuisance parameters and also the sensor noise variances. Details on how to solve the resulting low-dimensional non-linear least squares criterion are given, and how to extend the algorithms to target tracking. Explicit formulas for the Cramer-Rao lower bound are given for both localization and tracking.

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

[2]  Fredrik Gustafsson,et al.  Particle filters for positioning, navigation, and tracking , 2002, IEEE Trans. Signal Process..

[3]  Yu Hen Hu,et al.  Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array , 2003, EURASIP J. Adv. Signal Process..

[4]  N. Gordon,et al.  Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .

[5]  Yu Hen Hu,et al.  Energy based collaborative source localization using acoustic micro-sensor array , 2002, 2002 IEEE Workshop on Multimedia Signal Processing..

[6]  A. Urruela,et al.  A novel estimator and theoretical limits for in-car radio-location , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[7]  H. Koorapaty.  Barankin bounds for position estimation using received signal strength measurements , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[8]  F. Gustafsson,et al.  Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements , 2005, IEEE Signal Processing Magazine.

[9]  E. L. Lehmann,et al.  Theory of point estimation , 1950 .

[10]  Alfred O. Hero,et al.  Relative location estimation in wireless sensor networks , 2003, IEEE Trans. Signal Process..

[11]  X. R. Li,et al.  Survey of maneuvering target tracking. Part I. Dynamic models , 2003 .

[12]  Neil J. Gordon,et al.  Editors: Sequential Monte Carlo Methods in Practice , 2001 .

[13]  Kristine L. Bell,et al.  On Geolocation Accuracy with Prior Information in Nonlineofsight Environment , 2007 .

[14]  Timothy J. Robinson,et al.  Sequential Monte Carlo Methods in Practice , 2003 .

[15]  Andreas F. Molisch,et al.  Localization via Ultra- Wideband Radios , 2005 .

[16]  Fredrik Gustafsson,et al.  POSSIBILITIES AND FUNDAMENTAL LIMITATIONS OF POSITIONING USING WIRELESS COMMUNICATION NETWORKS MEASUREMENTS , 2004 .

[17]  Jacob Benesty,et al.  Passive acoustic source localization for video camera steering , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[18]  Hisashi Kobayashi,et al.  On geolocation accuracy with prior information in non-line-of-sight environment , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[19]  Hisashi Kobayashi,et al.  Cramér-Rao Lower bound for geolocation in non-line-of-sight environment , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[20]  Hisashi Kobayashi,et al.  On relation among time delay and signal strength based geolocation methods , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[21]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[22]  Fredrik Gustafsson,et al.  Particle filters for positioning in wireless networks , 2002, 2002 11th European Signal Processing Conference.

[23]  Andreu Urruela,et al.  A novel estimator and performance bound for time propagation and Doppler based radio-location , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[24]  Niclas Bergman.  Posterior Cramér-Rao Bounds for Sequential Estimation , 2001, Sequential Monte Carlo Methods in Practice.

[25]  A. Urruela,et al.  Efficient mobile location from time measurements with unknown variances in dynamic scenarios , 2004, IEEE 5th Workshop on Signal Processing Advances in Wireless Communications, 2004..