Localization Error Computation for RSSI Based Positioning System in VANETs

Waqas Ahmad, Sheeraz Ahmed, Najia Sheeraz, Ayub Khan, A. Ishtiaq, Malka Saba
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引用次数: 4

Abstract

Vehicular Ad-hoc Networks (VANETs) is the most eminent field nowadays in Intelligent Transportation System. Applications included emergency alerts, positioning, and tracking of vehicles. Vehicle Localization in municipal areas is a major issue for protection applications. Many solutions have been provided including Global Positioning Systems (GPS) but these applications do not provide accuracy. Hence, a novel approach has been proposed here known as Received Signal Strength (RSS) Based Localization which aims to find accurate location of a target vehicle. It provides communication with Road Side Units (RSUs) by receiving signal within its range, and finds the average RSS. After the RSS has been found it is aided to the RSS Based Localization algorithm which finds accurate location of the vehicle. The main factor of proposed algorithm is its high signal to noise ratio which is obtained from the closest RSU. After the location of the vehicle is found, its Cramer Rao Lower Bound is analyzed. All the simulations performed shows that our suggested RSS based Localization are better than others traditional least squares and weighted least squares techniques.
基于RSSI的VANETs定位系统定位误差计算
车辆自组织网络(VANETs)是当今智能交通系统中最引人注目的领域。应用程序包括紧急警报、定位和车辆跟踪。车辆在城市区域的定位是保护应用的一个主要问题。已经提供了许多解决方案,包括全球定位系统(GPS),但这些应用程序不提供精度。因此,本文提出了一种新的方法,即基于接收信号强度(RSS)的定位,旨在找到目标车辆的准确位置。它通过接收其范围内的信号与路旁单位(rsu)进行通信,并计算平均RSS。在找到RSS后,辅助基于RSS的定位算法找到车辆的准确位置。该算法的主要特点是高信噪比,信噪比是由最接近的RSU获得的。在找到车辆位置后,对其Cramer Rao下界进行分析。仿真结果表明,本文提出的基于RSS的定位方法优于传统的最小二乘和加权最小二乘方法。
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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