Node Localization Based on Incremental Lms Algorithm with Variable Step Size
| Autor: | Zhongyou Wang, Wenhua Dai, Mou Wu, Siping Hu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Least mean squares filter
Variable (computer science) Computer science Node (networking) Convergence (routing) Real-time computing 0202 electrical engineering electronic engineering information engineering Overhead (computing) 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology Network topology Wireless sensor network |
| Zdroj: | CSE/EUC (2) |
| DOI: | 10.1109/cse-euc.2017.205 |
| Popis: | A lot of work has been done to design algorithms that utilize three or more anchors to locate the unknownposition sensor nodes. In this paper, we propose a new sensor network node localization technique based on incremental LMS (least mean squared) distributed estimation algorithm with variable step size. In our network topology, the location-aware anchor nodes are deployed along the border of monitoring area and organized into a cycle where each anchor communicates only with its immediate neighbor. The positions of unknown nodes can be estimated by measuring the distance and direction vector between anchor nodes and unknown nodes. A recursive estimation method is used to enhance location accuracy with low communication overhead. Unlike traditional LMS algorithm with fixed step size, a variable step size strategy is utilized to achieve the tradeoff between location accuracy and convergence speed. Simulation results confirm the effectiveness of the proposed algorithm. |
| Databáze: | OpenAIRE |
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