یک الگوریتم محلی سازی ترکیبی
ترجمه نشده

یک الگوریتم محلی سازی ترکیبی

عنوان فارسی 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
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: مهندسی الگوریتم و محاسبات، شبکه های کامپیوتری
کلمات کلیدی فارسی: 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
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2951140
دانشگاه: College of Electronic Science, National University of Defense Technology, Changsha 410073, China
صفحات مقاله انگلیسی: 8
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 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
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13970
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

I. Introduction

II. System Model

III. Proposed Hybrid Localization Algorithm

IV. Simulation Result

V. Conclusion

Authors

Figures

References

بخشی از مقاله (انگلیسی)

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.