zbMATH — the first resource for mathematics

Acoustic source localization in wireless sensor network. (English) Zbl 1196.94036
Summary: We consider the problem of acoustic source localization in a wireless sensor network based on different measured signal quantities, such as the received signal strength (RSS), the angle of arrival (AOA) and the time of arrival (TOA). For each of these quantities, an appropriate weighted least squares criterion function is developed to be used for sound source localization. The weights of each criterion function take into account the decrease in the signal-to-noise ratio (SNR) with distance from the source. In addition, RSS localization algorithm proposed in this paper provides improvement of the localization accuracy for low SNR. Finally, separate criterion functions for RSS, TOA and AOA are used together to obtain minimal localization error and maximal reliability of the acoustic source localization. Simulation analysis confirms improved performance of the proposed localization algorithm.
94A13 Detection theory in information and communication theory
Full Text: DOI
[1] P. Aarabi, The fusion of distributed microphone arrays for sound localization. EURASIP J. Appl. Sign. Process., Spec. Issue Sens. Netw. 4, 338–347 (2003) · Zbl 1065.94518
[2] J.N. Asha, R.L. Mosesb, Acoustic time delay estimation and sensor network self-localization: experimental results. J. Acoust. Soc. Am. 118(2), 841–850 (2005) · doi:10.1121/1.1953307
[3] M.S. Brandstein, J.E. Adcock, H.F. Silverman, A localization-error-based method for microphone array design, in Proc. IEEE Int. Conf. Acoustic., Speech, Signal Processing, Atlanta, GA, (1996), pp. 901–904
[4] M.S. Brandstein, J.E. Adcock, H.F. Silverman, A closed-form location estimation for use with room environment microphone array. IEEE Trans. Speech Audio Process. 5, 45–50 (1997) · doi:10.1109/89.554268
[5] J.C. Chen, K. Yao, R.E. Hudson, Acoustic source localization and beamforming: theory and practice. EURASIP J. Appl. Sign. Process., Spec. Issue Sens. Netw. 4, 359–370 (2003) · Zbl 1065.94520
[6] K. Deng, Z. Liu, Weighted least-squares solutions for energy-based collaborative source localization using acoustic array. IJCSNS Int. J. Comput. Sci. Netw. Secur. 7(1), 159–165 (2007)
[7] J.H. DiBiase, H.F. Silverman, M.S. Brandstein, Robust localization in reverberant room, in Microphone Arrays, ed. by M.S. Brandstein, D. Ward (Springer, New York, 2001), pp. 157–180
[8] N. Iwakiri, T. Kobayashi, Ultra-wideband time-of-arrival and angle-of-arrival estimation using transformation between frequency and time domain signals. J. Commun. 3(1), 12–19 (2008)
[9] B. Kovačević, Ž. urović, Fundamentals of Stochastic Signals, Systems and Estimation Theory with Worked Examples (Academic Mind, Belgrade, 1999), ISBN 86-7466-007-x
[10] D. Li, Y.H. Hu, Energy-based collaborative source localization using acoustic microsensor array. EURASIP J. Appl. Sign. Process., Spec. Issue Sens. Netw. 4, 321–337 (2003) · Zbl 1065.94522
[11] L. Mailaender, On the geolocation bounds for round-trip time-of-arrival and all non-line-of-sight channels. EURASIP J. Adv. Sign. Process. 2008, 1–10
[12] G. Mao, B. Fidan, B.D.O. Anderson, Wireless sensor network localization techniques. Comput. Netw. 51, 2529–2553 (2007) · Zbl 1120.68021 · doi:10.1016/j.comnet.2006.11.018
[13] R.L. Moses, D. Krishnamurthy, R.M. Patterson, A self-localization method for wireless sensor networks. EURASIP J. Appl. Sign. Process., Spec. Issue Sens. Netw. 4, 348–358 (2003) · Zbl 1065.94524
[14] L.D. Nardis, M.-G.D. Benedetto, Joint communication, ranging, and positioning in low data-rate UWB networks, in Joint 2nd Workshop on Positioning, Navigation and Communication 2005, (WPNC’05) & 1st Ultra-Wideband Expert Talk (UET’05), March 17 2005, Hannover, Germany, pp. 191–200
[15] J.A. Nelder, R. Mead, A simplex method for function minimization. Comput. J. 7, 308–313 (1965) · Zbl 0229.65053
[16] M.M. Noel, P.P. Joshi, T.C. Jannett, Improved maximum likelihood estimation of target position in wireless sensor networks using particle swarm optimization, in Proceedings of the Third International Conference on Information Technology: New Generations (ITNG’06) (IEEE Computer Society, Los Alamitos, 2006), pp. 274–279
[17] N. Patwari, J.N. Ash, S. Kyperountas, A.O. Hero III, R.L. Moses, N.S. Correal, Locating the nodes. IEEE Sig. Process. Mag. 54–69 (2005)
[18] C.W. Reed, R.E. Hudson, K. Yao, Direct joint source localization and propagation speed estimation, in Proc. IEEE Int. Conf. Acoustic., Speech, Signal Processing, Phoenix, AZ (1999), pp. 1169–1172
[19] R.A. Saeed, S. Khatun, B.M. Ali, M.A. Khazani, Performance of ultra-wideband time-of-arrival estimation enhanced with synchronization scheme. ECTI Trans. Electr. Eng. Electron. Commun. 4(1), 78–84 (2006)
[20] R.O. Schmidt, Multiple emitter location and signal parameter estimation. IEEE Trans. Antennas Propag. 34(3), 276–280 (1986) · doi:10.1109/TAP.1986.1143830
[21] X. Sheng, Y.-H. Hu, Energy based acoustic source localization, in Information Processing in Sensor Networks, ed. by F. Zhao, L. Guibas (Springer, Berlin, 2003), pp. 285–300 · Zbl 1027.68941
[22] X. Sheng, Y.H. Hu, Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks. IEEE Trans. Sign. Process. 53(1), 44–53 (2005) · Zbl 1370.94349 · doi:10.1109/TSP.2004.838930
[23] H.L.V. Trees, Detection, Estimation, and Modulation Theory, Part I (Wiley, New York, 2002)
[24] H.L.V. Trees, Optimum Array Processing–Part IV (Wiley, New York, 2002)
[25] H. Urkowitz, Signal Theory and Random Processes (Artech House, Norwood, 1983) · Zbl 0173.46301
[26] X. Wang, D. Bi, L. Ding, S. Wang, Agent collaborative target localization and classification in wireless sensor networks. Sensors 7, 1359–1386 (2007) · doi:10.3390/s7081359
[27] K. Yao, F. Lorenzelli, Localization in sensor networks. ST J. Res. 4(1), 80–95 (2007). Wireless sensor networks, University of California, Los Angeles
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.