مقاله انگلیسی رایگان در مورد یک الگوریتم محلی سازی ترکیبی – IEEE 2019

 

مشخصات مقاله
ترجمه عنوان مقاله یک الگوریتم محلی سازی ترکیبی مبتنی بر زمان عزیمت (TOF) و اختلاف زمان ورود (TDOA) برای شبکه های حسگر بی سیم غیر هم زمان
عنوان انگلیسی مقاله A Hybrid Localization Algorithm Based on TOF and TDOA for Asynchronous Wireless Sensor Networks
انتشار مقاله سال 2019
تعداد صفحات مقاله انگلیسی 8 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
4.641 در سال 2018
شاخص H_index 56 در سال 2019
شاخص SJR 0.609 در سال 2018
شناسه ISSN 2169-3536
شاخص Quartile (چارک) Q2 در سال 2018
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های مرتبط مهندسی الگوریتم و محاسبات، شبکه های کامپیوتری
نوع ارائه مقاله
ژورنال
مجله / کنفرانس دسترسی – IEEE Access
دانشگاه  College of Electronic Science, National University of Defense Technology, Changsha 410073, China
کلمات کلیدی شبکه حسگر بی سیم، الگوریتم محلی سازی ترکیبی، اختلاف زمان ورود (TDOA)، زمان عزیمت (TOF)، تخمین انحراف زمانی
کلمات کلیدی انگلیسی  Wireless sensor network, hybrid localization algorithm, time-difference-of-arrival (TDOA), time-of-flight (TOF), clock skew estimation
شناسه دیجیتال – doi
https://doi.org/10.1109/ACCESS.2019.2951140
کد محصول  E13970
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
I. Introduction
II. System Model
III. Proposed Hybrid Localization Algorithm
IV. Simulation Result
V. Conclusion
Authors
Figures
References

 

بخشی از متن مقاله:
Abstract

Accuracy and energy consumption are two crucial assessment standards for localization systems. The positioning algorithm used in a single technique may not balance the accuracy and power problem due to its limitations. Moreover, the performance of the existing combined localization method is unsatisfactory. In this paper, taking the relative clock skew into account, we investigate the biased time-of-flight (TOF) compensation problem in the symmetric double-sided two-way ranging (SDS-TWR) method. We first estimate the relative clock skew among sensor nodes to improve the accuracy of the ranging result. We then combine with the time-difference-of-arrival (TDOA) algorithm and reduce the number of transmissions and receptions on the tag (a node that needs to be located) side. Finally, the tag location is determined by Newton’s iteration method. A simulation is implemented to validate our theoretical analysis and the results show that our proposed hybrid localization algorithm improves the locating accuracy significantly, compared with that of the C-TDOA method. Furthermore, the proposed hybrid localization algorithm can overcome the shortcoming of high power cost in the conventional TOF-based algorithm.

Introduction

At present, there is an increasing number of studies focusing on wireless sensor networks (WSNs), mainly due to their rich applications in environmental monitoring, internet of things (IoT), military purposes and so on [1]–[6]. Localization plays one of the most important roles in WSNs. This is because a large number of operations of WSNs require the accurate localization of the individual nodes as a priori information to know where the metrics were measured [7]–[12]. Although global positioning systems (GPSs) are well-known methods for source localization, the accuracy provided by GPS is not always sufficient in harsh environments (e.g., urban canyons and indoor scenes). Moreover, the terminals in GPS-based localization systems require GPS receivers, which are uneconomical and unrealistic [13], [14]. For this reason, many source node localization algorithms applied to wireless sensor networks have recently been proposed in the literature. Wireless sensor networks commonly contain two types of sensor nodes, referred to as anchor nodes and tag nodes. Anchors have perfectly known locations and are regarded as the referent nodes to locate tags. Tags have unknown locations and need to be located. The purpose of localization is to estimate the locations of tags via measurements among the sensor nodes [15]–[18]. In general, localization algorithms can be classified as rangebased methods and range-free methods. This paper pays attention to the range-based methods because they tend to provide better performances.

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