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:: Volume 7, Issue 2 (3-2021) ::
JNSEE 2021, 7(2): 108-129 Back to browse issues page
A new intelligent hybrid method based on Kalman filter and GRNN for low-cost INS/GNSS integration
Kazem Shokoohi-Mehr, Mohsen Farshad , Ramazan Havangi, Nasser Mehrshad
birjand university , mfarshad@birjand.ac.ir
Abstract:   (710 Views)
Due to the inefficiency of Kalman filter-based methods for combining low-cost inertial navigation system data and global satellite navigation systems when satellite signals are outage, the use of artificial intelligence techniques in integrated architecture has become a common issue. Therefore, in this paper, while presenting an effective hybrid architecture, the generalized regression neural network is used to predict the required observations of the Kalman filter at the event of long-term outage of satellite signals. In the proposed model, for training the neural network, the velocities and positions of the inertial system are considered as inputs and also the velocities and positions of the global positioning system are considered as network outputs. This approach, while being practical and operational, has reduced computational time and increased the accuracy and speed of training and network estimation. The simulation results show that due to the simple yet robust structure of the proposed architecture and of course the selection of an efficient multi-input-multi-output neural network with the ability to detect the effective relationship between inputs and specified outputs and consequently correct errors related to speeds and situations, inertial navigation system can be used for real-time navigation, self-reliant, with high reliability and accuracy.
Keywords: GRNN, Kalman filter, integrated navigation, GNSS outages
Full-Text [PDF 1412 kb]   (134 Downloads)    
Type of Study: Research | Subject: Control Applications
Received: 2020/09/13 | Accepted: 2021/01/26 | Published: 2021/08/2
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Shokoohi-Mehr K, Farshad M, Havangi R, Mehrshad N. A new intelligent hybrid method based on Kalman filter and GRNN for low-cost INS/GNSS integration. JNSEE. 2021; 7 (2) :108-129
URL: http://jnsee.sut.ac.ir/jnsee/article-1-355-en.html


Volume 7, Issue 2 (3-2021) Back to browse issues page
سامانه های غیرخطی در مهندسی برق Journal of Nonlinear Systems in Electrical Engineering
نشریه سامانه‌های غیرخطی در مهندسی برق در خصوص اصول اخلاقی انتشار مقاله، از توصیه‌های «کمیته بین‌المللی اخلاق نشر» موسوم به COPE و «منشور و موازین اخلاق پژوهش» مصوب معاونت پژوهش و فناوری وزارت علوم، تحقیقات و فناوری تبعیت می‌کند.
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