Abstract
It is quite important to obtain the sensor nodes location information in the underwater acoustic sensor networks localization. A method of acoustic sensor network node self-localization based on adaptive particle swarm optimization is proposed aiming at the stringent difficulties of the underwater acoustic sensor node localization and the shortage of standard particle swarm optimization (PSO) algorithm which is easily trapped into the local optimum. In the method, the global search ability and the local performance of the PSO algorithm are effectively improved by balancing the stochastic inertia weight. At the same time, the proposed method finds easy and elegant solutions to get rid of the local optimization by adopting the adaptive mutation strategy. The experimental results indicated that the new method can effectively solve the current problem in the underwater acoustic sensor node localization, and the pointing accuracy achieves 0.605m.
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Yao, J., Han, Y., Wang, L., Pan, J., Bai, P., Zhou, J. (2012). Acoustic Sensor Network Node Self-localization Based on Adaptive Particle Swarm Optimization. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_87
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DOI: https://doi.org/10.1007/978-3-642-33478-8_87
Publisher Name: Springer, Berlin, Heidelberg
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