Abstract
Positioning of the location information of wireless sensor network nodes is one of the key issues in wireless sensor network applications. The traditional node positioning method based on least-square algorithm heavily depends on the ranging accuracy, and therefore cannot guarantee high precision. This paper presents a new method for wireless sensor network node positioning based on nonlinear weighting least-square algorithm. Regarding ranging equation error-weighted sum as a whole, this method starts with the initial iteration point of stepwise refinement to explore the optimal solution and further reduces the positioning computational complexity by the simplification of the Taylor equation. Experimental results demonstrate that promising results have been achieved by using this method.
Highlights
Wireless sensor networks are widely used in military and industrial fields due to its strong ability to acquire information, high-level autonomy, broad coverage, long life cycle, and aniattenuation under harsh environment, and so forth
The traditional node positioning method based on least-square algorithm heavily depends on the ranging accuracy, and cannot guarantee high precision
This paper presents a new method for wireless sensor network node positioning based on nonlinear weighting least-square algorithm
Summary
Wireless sensor networks are widely used in military and industrial fields due to its strong ability to acquire information, high-level autonomy, broad coverage, long life cycle, and aniattenuation under harsh environment, and so forth. The traditional node positioning method based on leastsquare algorithm heavily depends on the ranging accuracy, and cannot guarantee an accurate positioning. This paper presents a new method for wireless sensor network node positioning based on nonlinear weighting least-square algorithm. The main contributions of this paper including: (1) introducing a channel propagation model for measuring the distance between unknown nodes and anchor nodes, and (2) enhancing measurement accuracy by the Gaussian filtering method. In this manner, this paper has improved wireless sensor network localization algorithm based on the weighted nonlinear least square to achieve high-precision positioning.
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