Accurate Attitude Determination Based on Adaptive UKF and RBF Neural Network Using Fusion Methodology for Micro-IMU Applied to Rotating Environment
المؤلفون المشاركون
Wang, Lei
Meng, Zhi Min
Guan, Ying
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-17، 17ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-07-31
دولة النشر
مصر
عدد الصفحات
17
التخصصات الرئيسية
الملخص EN
Focusing on the issue of attitude tracking for low-cost and small-size Micro-Electro-Mechanical System (MEMS) Inertial Measurement Unit (IMU) in high dynamic environment, an Adaptive Unscented Kalman Filter (AUKF) method combining sensor fusion methodology with Artificial Neural Network (ANN) is proposed.
The different control strategies are adopted by fusing multi-MEMS inertial sensors under various dynamic situations.
The AUKF attitude determination approach utilizing the MEMS sensor and Global Positioning System (GPS) can provide reliable estimation in these situations.
In particular, the adaptive scale factor is used to adaptively weaken or enhance the effects on new measurement data according to the predicted residual vector in the estimation process.
In order to solve the problem that the new measurement data is not available in case of GPS fault, an attitude algorithm based on Radial Basis Function (RBF)-ANN feedback correction is proposed for AUKF.
The estimated deviation of predicted system state can be provided based on RBF-ANN in GPS-denied environment.
The corrected predicted system state is used for the estimation process in AUKF.
An experimental platform was setup to simulate the rotation of the spinning projectile.
The experimental results show that the proposed method has better performance in terms of attitude estimation than other representative methods under various dynamic situations.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Lei& Meng, Zhi Min& Guan, Ying. 2020. Accurate Attitude Determination Based on Adaptive UKF and RBF Neural Network Using Fusion Methodology for Micro-IMU Applied to Rotating Environment. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1193362
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Lei…[et al.]. Accurate Attitude Determination Based on Adaptive UKF and RBF Neural Network Using Fusion Methodology for Micro-IMU Applied to Rotating Environment. Mathematical Problems in Engineering No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1193362
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Lei& Meng, Zhi Min& Guan, Ying. Accurate Attitude Determination Based on Adaptive UKF and RBF Neural Network Using Fusion Methodology for Micro-IMU Applied to Rotating Environment. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1193362
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1193362
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