Hopfield-neural-network-based filter design for INS/DS integrated navigation system

2003 ◽  
Author(s):  
Long Zhao ◽  
Zhe Chen
Keyword(s):  
Neural Network ◽  
Navigation System ◽  
Filter Design ◽  
Hopfield Neural Network ◽  
Integrated Navigation ◽  
Integrated Navigation System

Using Artificial Neural Networks to Compensate for the Error in an Integrated Navigation System

2020 ◽  
pp. 4-26
Author(s):  
N. Al Bitar ◽  
A.I. Gavrilov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Navigation System ◽  
Satellite Navigation ◽  
Satellite System ◽  
Integrated Navigation ◽  
Satellite Navigation System ◽  
Integrated Navigation System ◽  
Artificial Neural

The paper presents a new method for improving the accuracy of an integrated navigation system in terms of coordinate and velocity when there is no signal received from the global navigation satellite system. We used artificial neural networks to simulate the error occurring in an integrated navigation system in the absence of the satellite navigation system signal. We propose a method for selecting the inputs for the artificial neural networks based on the mutual information (MI) criterion and lag-space estimation. The artificial neural network employed is a non-linear autoregressive neural network with external inputs. We estimated the efficiency of using our method to solve the problem of compensating for the error in an integrated navigation system in the absence of the satellite navigation system signal

An Integrated Navigation System For Suez Canal (SCINS)

2003 ◽  
Vol 56 (2) ◽  
pp. 241-255 ◽  
Author(s):  
Farouk Abd EL-Kader ◽  
M. Samy Abo EL-Soud ◽  
Kamel EL-Serafy ◽  
Ezzat A. Hassan
Keyword(s):  
Real Time ◽  
Navigation System ◽  
Traffic Management ◽  
Filter Design ◽  
Suez Canal ◽  
System Level ◽  
Superior Performance ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Traffic Management System

This paper offers a designed Integrated Navigation System that will permit vessels to transit safely through the Suez Canal avoiding collision and grounding in all weather environments instead of being directed to anchor, thus keeping the Canal open at all times for ship transits. The Suez Canal Integrated Navigation System (SCINS) includes Differential Global Positioning System (DGPS), Suez Canal LORAN-C system, and Vessel Traffic Management System (VTMS). The combination of DGPS and LORAN-C systems would provide real-time DGPS corrections that could be used to calibrate the Loran fix; this can be achieved by means of portable integrated DGPS/LORAN-C sets installed aboard the vessels. The addition of VTMS provides significant capability for preserving system accuracy during periods of GPS outages. Due to the interface between LORAN-C and VTMS systems, the SCINS will be able to solve the problem of targets that cannot be tracked by VTMS radars in the shadow areas behind the new bridges along the Canal. The SCINS automates position fixing in real-time, offers a designed algorithm to return the ship to the middle of the Canal and computes the cross-track error (XTE) and the ship squat. Kalman Filter design and system level performance predictions for the SCINS are briefly described. Simulation results show that the SCINS offers superior performance and better position accuracy than current integrated systems.

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