Real time RSSI error reduction in distance estimation using RLS algorithm

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI:10.1109/IADCC.2013.6514305

R. Mehra, Ashutosh Kumar Singh

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引用次数: 28

Abstract

Recently received signal strength (RSS)-based distance estimation technique has been proposed as a low complexity, low-cost solution for mobile communication node with minimum RSSI error. After investigating the existing algorithm of location technique, it is observed that the distribution of RSSI-value at each sample point is fluctuant even in the same position due to shadow fading effect. Therefore, here present a novel method for RSSI error reduction in distance estimation using recursive least square (RLS)-algorithm to the existing deterministic algorithms. The proposed method collects RSSI-values from the mobile communication node to build the probability model. Once the probability models are estimated for different standard deviation related to path loss exponent using adaptive filtering in real time, it is possible to accurately determine the distance between the mobile communication node and fixed communication node. From simulation results it is shown, that the accuracy of RSSI-value for mobile communication node in real time distance estimation is improved in changing environments.

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利用RLS算法实时减小距离估计中的RSSI误差

近年来，基于接收信号强度(RSS)的距离估计技术作为一种低复杂度、低成本、RSSI误差最小的移动通信节点估计方法被提出。通过对现有定位技术算法的研究发现，即使在同一位置，由于阴影衰落效应，每个样本点的rssi值分布也是波动的。因此，本文提出了一种利用递推最小二乘(RLS)算法对现有确定性算法进行距离估计的RSSI误差减小的新方法。该方法收集移动通信节点的rssi值，建立概率模型。利用自适应滤波实时估计出与路径损耗指数相关的不同标准差的概率模型，就可以准确地确定移动通信节点与固定通信节点之间的距离。仿真结果表明，在变化的环境下，移动通信节点实时距离估计的rssi值精度得到了提高。

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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2013 3rd IEEE International Advance Computing Conference (IACC)

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