Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines
المؤلفون المشاركون
Zhang, Shen
Song, Boming
Long, Jia
Hu, Qingsong
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-10-09
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency.
The localization accuracy of a mine localization system is influenced by many factors.
The most significant factor is the non-line of sight (NLOS) propagation error of the localization signal between the access point (AP) and the target node (Tag).
In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm.
However, the traditional optimization algorithms are complex and exhibit poor optimization performance.
To solve this problem, this paper proposes a new method for mine time of arrival (TOA) localization based on the idea of comprehensive optimization.
The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance.
This proposed method combines the advantages of particle filtering and fingerprinting localization.
It reduces algorithm complexity and has better error suppression performance.
The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR) method or received signal strength indication (RSSI) based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Song, Boming& Zhang, Shen& Long, Jia& Hu, Qingsong. 2017. Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190107
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Song, Boming…[et al.]. Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1190107
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Song, Boming& Zhang, Shen& Long, Jia& Hu, Qingsong. Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190107
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1190107
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر