A range-based predictive localization algorithm for WSID networks

International Conference on Wireless and Optical Communications Pub Date : 2017-11-07 DOI:10.1117/12.2288849

Yuan Liu, Junjie Chen, Gang Li

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Abstract

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

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基于距离的WSID网络预测定位算法

定位算法的研究大多是在节点密集分布的传感器网络上进行的。然而，在传感器节点稀疏分布的网络中，容易出现不可定位问题。为了解决这一问题，本文提出了一种基于距离的无线传感器网络预测定位算法(RPLA)。建立了高斯混合模型来预测移动目标的弹道。然后，利用接收到的信号强度指示，基于近似三角点剖分测试算法减小目标位置的驻留面积。此外，还引入了协同定位方案，实现了非可定位情况下的目标定位。仿真结果验证了该算法对传感器节点稀疏分布的网络实现了准确的定位。RPLA的定位精度比APIT算法高48.7%，比基于单一高斯模型的算法高16.8%，比基于卡尔曼滤波的算法高10.5%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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International Conference on Wireless and Optical Communications

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