Path Planning and Localization for Mobile Anchor Based Wireless Sensor Networks

Date

2017-09-02

Author

Erdemir, Ecenaz
Tuncer, Temel Engin

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In wireless sensor networks, anchor positions play an important role for accurate localization. For mobile anchor ( MA) based scenarios, both the efficiency of the path planning algorithm and the accuracy of the localization mechanism are critical for the best performance. In this work, an adaptive path planning algorithm is proposed based on Gauss-Markov mobility model, while the sensors are localized using alternating minimization approach. Path planning, which combines the velocity adjustment, the perpendicular bisector and the virtual repulsive strategies, is improved by developing virtual attractive force strategy. The surveillance area is divided into grids and a virtual attractive force is applied to the MA in sparsely and densely populated areas. For localization, the non-convex optimization problem is converted into a bi-convex form and solved by alternating minimization algorithm leading to a shorter MA path. The simulation results show that introducing the virtual attractive strategy increases the path planning accuracy and cover more surveillance region using less energy. Furthermore, compared to the linear localization method, the localization accuracy increases when the alternating minimization is used.

Subject Keywords

Dynamic path planning, Mobility model, Mobile-anchor, Sensor network localization, Alternating minimization

URI

https://hdl.handle.net/11511/55477

Conference Name

25th European Signal Processing Conference (EUSIPCO)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

E. Erdemir and T. E. Tuncer, “Path Planning and Localization for Mobile Anchor Based Wireless Sensor Networks,” presented at the 25th European Signal Processing Conference (EUSIPCO), GREECE, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55477.