An Adaptive Localization Approach for Wireless Sensor Networks Based on Gauss-Markov Mobility Model

Zhong, Zhi; Luo, Dang; Liu, Shaoqiang; Fan, Xiaoping; Qu, Zhihua

doi:10.3724/sp.j.1004.2010.01557

Cited by 15 publications

(33 citation statements)

References 13 publications

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“…Hence, p n and d n are found in the neighboring range ofp andd [5]. Instead of moving with the mean pace, the MA velocity is adjusted according to the acknowledgments received from the sensors.…”

Section: A Velocity Adjustment Strategymentioning

confidence: 99%

“…Moreover, in static anchor scenarios, all anchor nodes become useless after the localization process. Hence, using a mobile anchor with the ability to broadcast its position decreases the cost of the localization [5]. In this work, a path planning algorithm based on Gauss-Markov (GM) mobility is proposed.…”

Section: Introductionmentioning

confidence: 99%

“…PATH PLANNING ALGORITHM In this work, an adaptive path planning algorithm based on the GM mobility model is proposed. As in [5], the model can be described by…”

Section: Introductionmentioning

confidence: 99%

“…When there is no guarantee for three or more neighboring anchors, localization problem can be solved by the proposed optimization algorithm effectively. In this work, limitations of the path planning algorithm in [5] are eliminated by proposing a virtual attractive force strategy and a novel optimization method for the localization.…”

Section: Introductionmentioning

confidence: 99%

“…In this work, a path planning algorithm based on Gauss-Markov (GM) mobility is proposed. In addition to the velocity adjustment, the perpendicular bisector and the virtual repulsive force strategies in [5], a virtual attractive force is defined in this paper to control the velocity and the direction of the mobile anchor. Besides, a sensor can be localized in 2-D, if there are at least three neighboring anchors in its communication range [6].…”

Section: Introductionmentioning

confidence: 99%

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Path planning and localization for mobile anchor based wireless sensor networks

Erdemir

Tuncer

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-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.

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Section: A Velocity Adjustment Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…PATH PLANNING ALGORITHM In this work, an adaptive path planning algorithm based on the GM mobility model is proposed. As in [5], the model can be described by…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations