A Novel Neural Network-Based SINSDVL Integrated Navigation Approach to Deal with DVL Malfunction for Underwater Vehicles
المؤلفون المشاركون
Li, Wanli
Chen, Mingjian
Zhang, Chao
Zhang, Lundong
Chen, Rui
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-07-26
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
A navigation grade Strapdown Inertial Navigation System (SINS) combined with a Doppler Velocity Log (DVL) is widely used for autonomous navigation of underwater vehicles.
Whether the DVL is able to provide continuous velocity measurements is of crucial importance to the integrated navigation precision.
Considering that the DVL may fail during the missions, a novel neural network-based SINS/DVL integrated navigation approach is proposed.
The nonlinear autoregressive exogenous (NARX) neural network, which is able to provide reliable predictions, is employed.
While the DVL is available, the neural network is trained by the body frame velocity and its increment from the SINS and the DVL measurements.
Once the DVL fails, the well trained network is able to forecast the velocity which can be used for the subsequent navigation.
From the experimental results, it is clearly shown that the neural network is able to provide reliable velocity predictions for about 200 s–300 s during DVL malfunction and hence maintain the short-term accuracy of the integrated navigation.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Wanli& Chen, Mingjian& Zhang, Chao& Zhang, Lundong& Chen, Rui. 2020. A Novel Neural Network-Based SINSDVL Integrated Navigation Approach to Deal with DVL Malfunction for Underwater Vehicles. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1194098
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Wanli…[et al.]. A Novel Neural Network-Based SINSDVL Integrated Navigation Approach to Deal with DVL Malfunction for Underwater Vehicles. Mathematical Problems in Engineering No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1194098
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Wanli& Chen, Mingjian& Zhang, Chao& Zhang, Lundong& Chen, Rui. A Novel Neural Network-Based SINSDVL Integrated Navigation Approach to Deal with DVL Malfunction for Underwater Vehicles. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1194098
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1194098
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