基于距离区间概率测距的无线传感器网络定位算法研究

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摘要基于经验的传播模型在实际应用中存在多值问题，导致RSSI 与距离并非一一映射。本文提出了一种改进的 MDS-MAP 定位算法，该算法利用基于距离区间概率的测距模型，消除多值问题对测距模型精度的影响，从而提高测距模型的测量精度。通过仿真结果表明，改进的算法与传统的MDS-MAP 定位算法相比，算法具有更好的定位精度。

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	胡良梁

关键词 ：无线传感器网络, 测距模型, 接收信号强度, 多值问题, MDS-MAP 方法

Abstract：The propagation model based on experience has multi-valued problems in the practical application, which causes the RSSI and the distance not one- to-one mapping. This paper proposes an improved MDS-MAP localization algorithm, which uses propagation model based on distance interval ranging probability to eliminate the influence of multi-valued problems to ranging accuracy of the model, thereby improving measurement accuracy of ranging model. The simulation results show that the improved algorithm has better positioning accuracy when compared with the traditional MDS - MAP localization algorithm.

Key words： wireless sensor network ranging model received signal strength indicator multi- valued problems MDS-MAP scheme

年卷期日期: 2015-05-10 出版日期: 1900-01-01

ZTFLH:

TP393

基金资助:重庆市教委科技项目，项目编号：No.KJ1401403。

作者简介: 胡良梁，男，湖南人，硕士研究生，研究方向: 无线传感器网络。

引用本文:

胡良梁. 基于距离区间概率测距的无线传感器网络定位算法研究[J]. 电脑与电信, 2015, 1(5): 13-23.
Hu Liangliang. Localization Algorithm Based on the Distance Probability ofWireless Sensor Networks. Computer & Telecommunication, 2015, 1(5): 13-23.

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http://www.computertelecom.com.cn/CN/ 或 http://www.computertelecom.com.cn/CN/Y2015/V1/I5/13