The Community for Technology Leaders
RSS Icon
Issue No.04 - April (2012 vol.11)
pp: 567-576
Xingbo Wang , Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
Huanshui Zhang , Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
A common technical difficulty in target tracking in a wireless sensor network is that individual homogeneous sensors only measure their distances to the target whereas the state of the target composes of its position and velocity in the Cartesian coordinates. That is, the senor measurements are nonlinear in the target state. Extended Kalman filtering is a commonly used method to deal with the nonlinearity, but this often leads to unsatisfactory or even unstable tracking performances. In this paper, we present a new target tracking approach which avoids the instability problem and offers superior tracking performances. We first propose an improved noise model which incorporates both additive noises and multiplicative noises in distance sensing. We then use a maximum likelihood estimator for prelocalization to remove the sensing nonlinearity before applying a standard Kalman filter. The advantages of the proposed approach are demonstrated via experimental and simulation results.
wireless sensor networks, distance measurement, Kalman filters, maximum likelihood estimation, radiofrequency measurement, target tracking, maximum likelihood estimator, wireless sensor networks, target tracking, MLE, KF, distance measurements, Cartesian coordinates, extended Kalman filtering, instability problem, improved noise model, multiplicative noises, additive noises, distance sensing, Sensors, Noise, Wireless sensor networks, Target tracking, Noise measurement, Kalman filters, Maximum likelihood estimation, extended Kalman filtering., Target tracking, wireless sensor networks, maximum likelihood estimation
Xingbo Wang, Huanshui Zhang, "Target Tracking in Wireless Sensor Networks Based on the Combination of KF and MLE Using Distance Measurements", IEEE Transactions on Mobile Computing, vol.11, no. 4, pp. 567-576, April 2012, doi:10.1109/TMC.2011.59
[1] M. Tubaishat and S. Madria, “Sensor Networks: An Overview,” IEEE Potentials, vol. 22, no. 2, pp. 20-23, Apr./May 2003.
[2] A. Bharathidasan and V.A.S. Pondur, “Sensor Networks: An Overview,” technical report, Univ. of California, Davis, 1999.
[3] D. Estrin, L. Girod, G. Pottie, and M. Srivastava, “Instrumenting the World with Wireless Sensor Networks,” Proc. Int'l Conf. Acoustics, Speech, and Signal Processing (ICASSP '01), pp. 2685-2678, May 2001.
[4] C. Otto, A. Milenkovic, C. Sanders, and E. Jovanov, “System Architecture of a Wireless Body Area Sensor Network for Ubiquitous Health Monitoring,” J. Mobile Multimedia, vol. 1, no. 4, pp. 307-326, 2006.
[5] N. Patwari and A.O. HeroIII, “Location Estimation Accuracy in Wireless Sensor Networks,” Proc. Asilomar Conf. Signals and Systems, Nov. 2002.
[6] N. Patwari, A.O. Hero, M. Perkins, N.S. Correal, and R.J. O'Dea, “Relative Location Estimation in Wireless Sensor Networks,” IEEE Trans. Signal Processing, vol. 51, no. 8, pp. 2137-2148, Aug. 2003.
[7] N. Patwari, J. Ash, S. Kyperountas, A. Hero, R. Moses, and N.S. Correal, “Locating the Nodes: Cooperative Localization in Wireless Sensor Networks,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 54-69, July 2005.
[8] R. Zemek, S. Hara, K. Yanagihara, and K. Kitayama, “A Joint Estimation of Target Location and Channel Model Parameters in an IEEE 802.15.4-Based Wireless Sensor Network,” Proc. 18th IEEE Int'l Symp. Personal, Indoor and Mobile Radio Comm. (PIMRC '07), pp. 1-5, Sept. 2007.
[9] X. Sheng and Y. Hu, “Energy Based Source Localization,” Proc. Second Int'l Conf. Information Processing Sensor Networks (IPSN '03), pp. 285-300, 2003.
[10] L. Girod, M. Lukac, V. Trifa, and D. Estrin, “The Design and Implementation of a Self-Calibrating Acoustic Sensing Platform,” Proc. ACM Fourth Int'l Conf. Embedded Networked Sensor Systems (SenSys), Nov. 2006.
[11] A. Savvides, C.C. Han, and M. Srivastava, “Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors,” Proc. ACM MobiCom, pp. 166-179, July 2001.
[12] N. Dragos and B. Nath, “Ad Hoc Positioning System (APS) Using AoA,” Proc. IEEE INFOCOM, pp. 1734-1743, Mar. 2003.
[13] M. McGuire, K.N. Plataniotis, and A.N. Venetsanopoulos, “Data Fusion of Power and Time Measurements for Mobile Terminal Location,” IEEE Trans. Mobile Computing, vol. 4, no. 2, pp. 142-153, Mar./Apr. 2005.
[14] C. Li and W. Zhuang, “Hybrid TDOA/AOA Mobile User Location for Wideband CDMA Cellular Systems,” IEEE Trans. Wireless Comm., vol. 1, no. 3, pp. 439-447, July 2002.
[15] Z. Gu and E. Gunawan, “Radiolocation in CDMA Cellular System Based on Joint Angle and Delay Estimation,” Wireless Personal Comm., vol. 23, no. 3, pp. 297-309, 2002.
[16] T. Kleine-Ostmann and A.E. Bell, “A Data Fusion Architecture for Enhanced Position Estimation in Wireless Networks,” IEEE Comm. Letters, vol. 5, no. 8, pp. 343-345, Aug. 2001.
[17] N. Thomas, D. Cruickshank, and D. Laurenson, “Performance of TDOA-AOA Hybrid Mobile Location System,” Proc. Int'l Conf. 3G Mobile Comm. Technologies, pp. 216-220, 2001.
[18] P. Bahl and V. Padmanabhan, “An in Building RF-Based User Location and Tracking System,” Proc. IEEE INFOCOM, pp. 775-784, Mar. 2000.
[19] C. Liu, K. Wu, and T. He, “Sensor Localization with Ring Overlapping Based on Comparison of Received Signal Strength Indicator,” Proc. IEEE Mobile Ad-Hoc and Sensor Systems (MASS), pp. 516-518, Oct. 2004.
[20] R.R. Brooks, C. Griffin, and D.S. Friedlander, “Self-Organized Distributed Sensor Network Entity Tracking,” Int'l J. High Performance Computing Applications, vol. 16, no. 3, pp. 207-220, Aug. 2002.
[21] J. Moore, T. Keiser, R.R. Brooks, S. Phoha, D. Friedlander, J. Koch, A. Reggio, and N. Jacobson, “Tracking Targets with Self-Organizing Distributed Ground Sensors,” Proc. IEEE Areospace Conf., vol. 5, pp. 2113-2123, 2003.
[22] L.M. Kaplan, “Global Node Selection for Localization in a Distributed Sensor Network,” IEEE Trans. Aerospace Electronics Systems, vol. 42, no. 1, pp. 113-135, Jan. 2006.
[23] W. Xiao, L. Xie, J. Chen, and L. Shue, “Multi-Step Adaptive Sensor Scheduling for Target Tracking in Wireless Sensor Networks,” Proc. IEEE Int'l Conf. Acoustics, Speech and Signal Processing (ICASSP), pp. 705-708, May 2006.
[24] Y. Liu and Z. Sun, “EKF-Based Adaptive Sensor Scheduling for Target Tracking,” Proc. IEEE Int'l Symp. Information Science and Eng. (ISISE), vol. 2, pp. 171-174, Dec. 2008.
[25] J. Lin, W. Xiao, F. Lewis, and L. Xie, “Energy-Efficient Distributed Adaptive Multisensor Scheduling for Target Tracking in Wireless Sensor Networks,” IEEE Trans. Instrumentation and Measurement, pp. 1-11, Oct. 2008.
[26] S. Julier and J. Uhlmann, “Unscented Filtering and Nonlinear Estimation,” Proc. IEEE, vol. 92, no. 3, pp. 401-422, Mar. 2004.
[27] X.R. Li and V.P. Jilkov, “A Survey of Maneuvering Target Tracking-Part III: Measurement Models,” Proc. SPIE Conf. Signal and Data Processing of Small Targets, pp. 423-446, July/Aug. 2001.
[28] Y. Bar-Shalom, X.R. Li, and T. Kirubarajan, Estimation with Application to Tracking and Navigation. John Wiley, 2001.
[29] Z.L. Zhao, X.R. Li, and V.P. Jilkov, “Best Linear Unbiased Filtering with Nonlinear Measurements for Target Tracking,” IEEE Trans. Aerospace Electronic Systems, vol. 40, no. 4, pp. 1324-1336, Oct. 2004.
[30] G. Zhou, T. He, S. Krishnamurthy, and J. Stankovic, “Models and Solutions for Radio Irregularity in Wireless Sensor Networks,” ACM Trans. Sensor Networks, vol. 2, no. 2, pp. 221-262, 2006.
[31] T. He, S. Krishnamurthy, J.A. Stankovic, T. Abdelzaher, L. Luo, R. Stoleru, T. Yan, L. Gu, G. Zhou, J. Hui, and B. Krogh, “VigilNet: An Integrated Sensor Network System for Energy-Efficient Surveillance,” ACM Trans. Sensor Networks, vol. 2, no. 1, pp. 1-38, Feb. 2006.
[32] M. Keally, G. Zhou, and G. Xing, “Watchdog: Confident Event Detection in Heterogeneous Sensor Networks,” Proc. IEEE 16th Real-Time Embedded Technology and Applications Symp. (RTAS '10), 2010.
[33] X. Sheng and Y.H. Hu, “Maximum Likelihood Multiple-Source Localization Using Acoustic Energy Measurements with Wireless Sensor Networks,” IEEE Trans. Signal Processing, vol. 53, no. 1, pp. 44-53, Jan. 2005.
[34] R.L. Moses, D. Krishnamurthy, and R. Patterson, “A Self-Localization Method for Wireless Sensor Networks,” EURASIP J. Applications Signal Processing, Special Issue on Sensor Networks, vol. 4, pp. 348-358, Mar. 2003.
[35] M. Noel, P. Joshi, and T. Jannett, “Improved Maximum Likelihood Estimation of Target Position in Wireless Sensor Networks Using Particle Swarm Optimization,” Proc. Third Int'l Conf. Information Technology: New Generations, Apr. 2006.
[36] M.G. Rabbat and R.D. Nowak, “Decentralized Source Localization and Tracking,” Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 3, pp. 921-924, May 2004.
[37] T. Zhao and A. Nehorai, “Information-Driven Distributed Maximum Likelihood Estimation Based on Gauss-Newton Method in Wireless Sensor Networks,” IEEE Trans. Signal Processing, vol. 55, no. 9, pp. 4669-4682, Sept. 2007.
[38] S. Banerjee and S. Khuller, “A Clustering Scheme for Hierarchical Control in Multi-Hop Wireless Networks,” Proc. IEEE INFOCOM, Apr. 2001.
[39] C. Lin and M. Gerla, “Adaptive Clustering for Mobile Wireless Networks,” IEEE J. Select Areas Comm., vol. 15, no. 7, pp. 1265-1275, July 1997.
[40] W.-P. Chen, J.C. Hou, and L. Sha, “Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks,” IEEE Trans. Mobile Computing, vol. 3, no. 3, pp. 258-271, July 2004.
[41] G.E. Forsythe, M.A. Malcolm, and C.B. Moler, Computer Methods for Mathematical Computations. Prentice-Hall, 1977.
[42] B.D.O. Anderson and J.B. Moore, Optimal Filtering. Prentice-Hall, 1979.
[43] The Cricket Indoor Location System, http:/cricket., 2011.
[44] X.R. Li and V.P. Jilkov, “A Survey of Maneuvering Target Tracking¨CPart IV: Decision-Based Methods,” Proc. SPIE Conf. Signal and Data Processing of Small Targets, pp. 511-534, Apr. 2002.
[45] J. Ru, V.P. Jilkov, X.R. Li, and A. Bashi, “Detection of Target Maneuver Onset,” IEEE Trans. Aerospace and Electronic Systems, vol. 45, no. 2, pp. 536-554, Apr. 2009.
27 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool