Low complexity least-square estimator for RSS-based localization in Wireless Sensor Networks

A. I. Alhasant, B. Sharif, C. Tsimenidis, J. Neasham
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引用次数: 5

Abstract

This paper presents an efficient Received Signal Strength RSS-based localization approach utilizing a Tree Search Algorithm (TSA). In comparison to the existing exhaustive search algorithms, e.g. Least Square Estimators (LSE) and Error Controlling localization (Ecolocation), the proposed approach achieves considerable reduction in computational complexity and storage requirements. The effectiveness of the TSA is evaluated through simulation and real experiments. The presented results show that the performance of the new approach closely achieves LSE and performs better than Ecolocation algorithms. Moreover, at a comparable system complexities, TSA outperforms the simplistic Proximity and Centroid localization algorithms.
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无线传感器网络中基于rss定位的低复杂度最小二乘估计
本文利用树搜索算法(TSA)提出了一种有效的基于接收信号强度rss的定位方法。与现有的穷举搜索算法(如Least Square Estimators (LSE)和Error control localization (Ecolocation))相比,该方法大大降低了计算复杂度和存储需求。通过仿真和实际实验对TSA的有效性进行了评价。实验结果表明,该方法的性能接近LSE,且优于生态定位算法。此外,在相当的系统复杂性下,TSA优于简单的接近和质心定位算法。
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