Global node selection for localization in a distributed sensor network

This work considers the problem of selecting the best nodes for localizing (in the mean squared (MS) position error sense) a target in a distributed wireless sensor network. Each node consists of an array of sensors that are able to estimate the direction of arrival (DOA) to a target. Different computationally efficient node selection approaches that use global network knowledge are introduced. Performance bounds based on the node/target geometry are derived, and these bounds help to determine the necessary communication reach of the active nodes. The resulting geolocation performance and energy usage, based on communication distance, is evaluated for a decentralized extended Kalman filter (EKF) that is exploiting the different selection approaches.

[1]  Branko Ristic,et al.  Cramer-Rao bound for nonlinear filtering with Pd<1 and its application to target tracking , 2002, IEEE Trans. Signal Process..

[2]  Feng Zhao,et al.  Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks , 2002, Int. J. High Perform. Comput. Appl..

[3]  Vikram Krishnamurthy,et al.  Algorithms for optimal scheduling and management of hidden Markov model sensors , 2002, IEEE Trans. Signal Process..

[4]  Mihail L. Sichitiu,et al.  Localization in Wireless Sensor Networks: A Probabilistic Approach , 2003, International Conference on Wireless Networks.

[5]  Wilson.  A turbulence spectral model for sound propagation in the atmosphere that incorporates shear and buoyancy forcings , 2000, The Journal of the Acoustical Society of America.

[6]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .

[7]  Yaakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking , 1995 .

[8]  Y. Oshman,et al.  Optimization of observer trajectories for bearings-only target localization , 1999 .

[9]  L.M. Kaplan,et al.  Local node selection for localization in a distributed sensor network , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[10]  L.A. Kaplan.  Transmission range control during autonomous node selection for wireless sensor networks , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[11]  R. G. Stansfield,et al.  Statistical theory of d.f. fixing , 1947 .

[12]  Volkan Cevher,et al.  Sensor array calibration via tracking with the extended Kalman filter , 2001, SPIE Defense + Commercial Sensing.

[13]  Lance M. Kaplan,et al.  On exploiting propagation delays for passive target localization using bearings-only measurements , 2005, J. Frankl. Inst..

[14]  H.F. Durrant-Whyte,et al.  On sensor management in decentralized data fusion , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[15]  Malcolm J. Crocker,et al.  Handbook of Acoustics , 1998 .

[16]  H. F. Durrant-Whyte,et al.  Fully decentralised algorithm for multisensor Kalman filtering , 1991 .

[17]  Feng Zhao,et al.  Information-driven dynamic sensor collaboration , 2002, IEEE Signal Process. Mag..

[18]  Camillo J. Taylor,et al.  A framework for sensor planning and control with applications to vision guided multi-robot systems , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[19]  Carlos H. Muravchik,et al.  Posterior Cramer-Rao bounds for discrete-time nonlinear filtering , 1998, IEEE Trans. Signal Process..

[20]  Saurabh Ganeriwal,et al.  Timing-sync protocol for sensor networks , 2003, SenSys '03.

[21]  N. Peach,et al.  Bearings-only tracking using a set of range-parameterised extended Kalman filters , 1995 .

[22]  J. Elson,et al.  Fine-grained network time synchronization using reference broadcasts , 2002, OSDI '02.

[23]  Alfonso Farina,et al.  Target tracking with bearings - Only measurements , 1999, Signal Process..

[24]  J. Cadre,et al.  Optimal observer trajectory in bearings-only tracking for manoeuvring sources , 1999 .

[25]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[26]  L. M. Kaplan.  Node selection for target tracking using bearing measurements from unattended ground sensors , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[27]  D. Lerro,et al.  Bias compensation for improved recursive bearings-only target state estimation , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[28]  Gregory J. Pottie,et al.  Instrumenting the world with wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[29]  Mani Srivastava,et al.  Energy-aware wireless microsensor networks , 2002, IEEE Signal Process. Mag..

[30]  Randolph L. Moses,et al.  A Self-Localization Method for Wireless Sensor Networks , 2003, EURASIP J. Adv. Signal Process..

[31]  Yingyu Wan,et al.  Accurate Time Synchronization for Wireless Sensor Networks , 2005, MSN.

[32]  D K Wilson,et al.  Performance bounds for passive sensor arrays operating in a turbulent medium: plane-wave analysis. , 2003, The Journal of the Acoustical Society of America.

[33]  Kung Yao,et al.  Acoustic Source Localization and Beamforming: Theory and Practice , 2003, EURASIP J. Adv. Signal Process..

[34]  Péter Molnár,et al.  Maximum likelihood methods for bearings-only target localization , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[35]  Feng Zhao,et al.  Collaborative In-Network Processing for Target Tracking , 2003, EURASIP J. Adv. Signal Process..

[36]  Jerry M. Mendel,et al.  Lessons in digital estimation theory , 1986 .

[37]  Ivan Kadar.  Optimum geometry selection for sensor fusion , 1998, Defense, Security, and Sensing.

[38]  Ivan Kadar,et al.  Self-organizing cooperative sensor network for remote surveillance: target tracking while optimizing the geometry between bearing-reporting sensors and the target , 2001, SPIE Defense + Commercial Sensing.

[39]  Robin J. Evans,et al.  An information theoretic approach to observer path design for bearings-only tracking , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

[40]  Tien Pham,et al.  Simulation of detection and beamforming with acoustical ground sensors , 2002, SPIE Defense + Commercial Sensing.

[41]  Mihail L. Sichitiu,et al.  Simple, accurate time synchronization for wireless sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[42]  Kung Yao,et al.  Source localization and beamforming , 2002, IEEE Signal Process. Mag..

[43]  Tien Pham,et al.  Adaptive wideband aeroacoustic array processing , 1996, Proceedings of 8th Workshop on Statistical Signal and Array Processing.

[44]  Samuel S. Blackman,et al.  Multiple-Target Tracking with Radar Applications , 1986 .

[45]  J. McClellan,et al.  Acoustic node calibration using a moving source , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[46]  Yaakov Bar-Shalom,et al.  Multitarget-multisensor tracking: Advanced applications , 1989 .

[47]  Yu Hen Hu,et al.  Detection, classification, and tracking of targets , 2002, IEEE Signal Process. Mag..

[48]  J.H. McClellan,et al.  Multiple-mode Kalman filtering with node selection using bearings-only measurements , 2004, Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the.