Neural Network Assisted Vector Tracking Loop for Bridging GPS Signal Outages

2015 ◽  
Vol 764-765 ◽  
pp. 560-564
Author(s):  
Dah Jing Jwo ◽  
Zi Ming Wen
Keyword(s):  
Neural Network ◽  
Navigation System ◽  
Doppler Frequency ◽  
Numerical Control ◽  
Tracking Loop ◽  
The Neural Network ◽  
Solid Objects ◽  
Global Positioning ◽  
Vector Tracking ◽  
Improved Performance

Signal blockage and reflections from buildings and other large, solid objects can lead to accuracy degradation. One of the merits of the Global Positioning System (GPS) vector tracking loop (VTL) architectures is that the tracking loop can be assisted in such degraded signal environments. This paper proposes the incorporation of the neural network (NN) into the VTL for improving the positioning quality. The NN is used to bridge the GPS signal and prevent the error growth due to signal outage from spreading into the entire tracking loop. The NNs are employed for predicting adequate numerical control oscillator (NCO) inputs, i.e., providing better prediction of residuals for the Doppler frequency and code phase in order to maintain regular operation of the navigation system. The NN-assisted VTL demonstrates the capability to ensure proper functioning of navigation system. Results show that the NN-assisted VTL can effectively provide improved performance during degraded signal environments such as GPS outages.

scholarly journals Vector tracking loop assisted by the neural network for GPS signal blockage

2015 ◽  
Vol 39 (19) ◽  
pp. 5949-5968 ◽  
Author(s):  
Dah-Jing Jwo ◽  
Zi-Ming Wen ◽  
Yu-Chuan Lee
Keyword(s):  
Neural Network ◽  
Tracking Loop ◽  
The Neural Network ◽  
Vector Tracking

Implementation and Performance Assessment of a Vector Tracking Method Based on a Software GPS Receiver

2011 ◽  
Vol 64 (S1) ◽  
pp. S151-S161 ◽  
Author(s):  
Sihao Zhao ◽  
Mingquan Lu ◽  
Zhenming Feng
Keyword(s):  
Global Positioning System ◽  
Carrier Frequency ◽  
Gps Receiver ◽  
Tracking Loop ◽  
Frequency Tracking ◽  
Tracking Method ◽  
Global Positioning ◽  
Vector Tracking ◽  
Tracking Loops ◽  
And Performance

A number of methods have been developed to enhance the robustness of Global Positioning System (GPS) receivers when there are a limited number of visible satellites. Vector tracking is one of them. It utilizes information from all channels to aid the processing of individual channels to generate receiver positions and velocities. This paper analyzes relationships among code phase, carrier frequency, and receiver position and velocity, and presents a vector loop-tracking algorithm using an Extended Kalman filter implemented in a Matlab-based GPS software receiver. Simulated GPS signals are generated to test the proposed vector tracking method. The results show that when some of the satellites are blocked, the vector tracking loop provides better carrier frequency tracking results for the blocked signals and produces more accurate navigation solutions compared with traditional scalar tracking loops.

Integrated Navigation of Mobile Robot Based on Neural Network and Fault Detection

2012 ◽  
Vol 433-440 ◽  
pp. 3175-3180
Author(s):  
Hong Mei Wang ◽  
Ming Lu Zhang ◽  
Guang Zhu Meng
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Global Positioning System ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Integrated Navigation ◽  
Global Positioning ◽  
Navigation Accuracy

When global positioning system (GPS) signal outages, the integrated navigation accuracy of GPS and strap-down inertial navigation system (SINS) will decline with time, and even navigation system cannot work. To avoid this, a new design is introduced. When GPS works normally, square root filter estimates the errors of position, velocity and attitude and compensates the outputs of SINS. When GPS is out of order, back propagation neural network (BPNN) will take the place of GPS to calculate the error parameters, thus the accuracy of navigation will enhance. And in this paper, the unit of fault detection is added to detect whether GPS signal outages or not. The simulation results show the effectiveness of this method

scholarly journals The Advanced Algorithmic Method for Navigation System Correction of Spacecraft

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Danhe Chen ◽  
K. A. Neusypin ◽  
Xiang Zhang ◽  
Chuangge Wang
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Navigation System ◽  
Parallel Implementation ◽  
The Self ◽  
Self Organization ◽  
Error Prediction ◽  
Measurement Systems ◽  
The Neural Network ◽  
Autonomous Mode

In this paper an advanced method for the navigation system correction of a spacecraft using an error prediction model of the system is proposed. Measuring complexes have been applied to determine the parameters of a spacecraft and the processing of signals from multiple measurement systems is carried out. Under the condition of interference in flight, when the signals of external system (such as GPS) disappear, the correction of navigation system in autonomous mode is considered to be performed using an error prediction model. A modified Volterra neural network based on the self-organization algorithm is proposed in order to build the prediction model, and the modification of algorithm indicates speeding up the neural network. Also, three approaches for accelerating the neural network have been developed; two examples of the sequential and parallel implementation speed of the system are presented by using the improved algorithm. In addition, simulation for a returning spacecraft to atmosphere is performed to verify the effectiveness of the proposed algorithm for correction of navigation system.

INS/GPS Integrated Navigation Method Based on Neural Network

2013 ◽  
Vol 712-715 ◽  
pp. 2419-2422
Author(s):  
Tian Lai Xu
Keyword(s):  
Neural Network ◽  
Global Positioning System ◽  
Inertial Navigation System ◽  
Integrated Navigation ◽  
Positioning Accuracy ◽  
Navigation Solution ◽  
Attitude Error ◽  
The Neural Network ◽  
Global Positioning ◽  
Navigation Method

Inertial Navigation System (INS) and Global Positioning System (GPS) are commonly integrated to overcomes each systems inadequacies and provide an accurate navigation solution. However, the positioning accuracy deteriorates with time in the absence of GPS signals. This paper proposed an artificial neural network aided INS/GPS integrated navigation method to bridge the GPS outages. In this method, the neural network was trained to model the error of INS when GPS was available. INS velocity and attitude error were got by implementing the neural network when GPS outages occurred. Simulations in INS/GPS integrated navigation showed improvement in positioning accuracy for GPS outages.

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