Analysis and Design of Simulation System for Passive Acoustic Senor Network

Abstract:

The simulation system for passive acoustic sensor network is an important part of information fusion system. Its main function is to simulate the detection process of acoustic sensor network and produce the simulation data which is needed for testing and evaluating the target tracking algorithms. For implementation of simulation system, the target motion model and the measurement model of passive acoustic sensor must be built, and a scenario will be defined in advance when it is running. This paper discussed the passive acoustic sensor network model and gave an information fusion system structure for passive acoustic sensor network. Then the basic principle of target detection for acoustic sensor is stated. Finally, we illustrated the operation process of a simulation system for passive acoustic sensor network.

• Periodical: Applied Mechanics and Materials (Volume 533)
• Pages: 214-217
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.533.214
• Online since: February 2014
• Authors: Jun Hua Li, Hong Wei Quan*, Xiu Yin Xue
• Keywords: Acoustic Sensor Network, Information Fusion, Simulation System, Target Tracking

References

[1] Kim, J. J., Linas, T. Large scale simulation of a distributed target tracking system. Proceedings of the Fifth International Conference on Information Fusion, 2002, Vol. 1, 624-629.

[2] Collier, S. L., Wilson, D. K. Performance bounds for passive sensor arrays operating in a turbulent medium: plane-wave analysis. Journal of the Acoustical Society of America, 2003, 113(5): 2704-2718.

DOI: 10.1121/1.1554691

[3] Ferguson, B., Lo, K. Turboprop and rotary-wing aircraft flight parameter estimation using both narrowband and broadband passive acoustic signal processing methods [J]. Journal of Acoustic Society of America, 2000, 108(4): 1763-1771.

DOI: 10.1121/1.1286150

[4] Lin, Y. S. Study on Multiple Moving Targets Passive Tracking and Data Association Algorithms. Ph. D Dissertation: Zhejiang University, (2003).

[5] Hue, C., Cadre, J. P. Sequential Monte Carlo methods for multiple target tracking and data fusion. IEEE Transactions on Signal Processing, 2002, 50(2): 309-325.

DOI: 10.1109/78.978386

[6] Zhang, R. Z., Wang, J. Z., Xue, A. K. Simulation system for passive acoustic detection network. Journal of Hangzhou Dianzi University, 2005, 25(2): 33-36.

[7] Degen, U., Remez, V. A test bed for sensor suite and multi sensor tracking algorithms studies. Information Fusion, 2000, Vol. 2, 15-19.

DOI: 10.1109/ific.2000.859886

[8] Sun, H. Y., Mao, S. Y., S. Li, H. The property of an algorithm for hierarchical fusion of multisensor data. Chinese Journal of Electronics, 1995, 4(4): 45-52.

[9] Wang, G. H., He, Y., Yang, Z. Adaptive sensor management in multisensor data fusion systems. Chinese Journal of Electronics, 1998, 8(2): 136-139.