A novel matrix block algorithm based on cubature transformation fusing variational Bayesian scheme for position estimation applied to MEMS navigation system

2022 ◽  
Vol 166 ◽  
pp. 108486
Author(s):  
Haoqian Huang ◽  
Jiacheng Tang ◽  
Rui Song ◽  
Xinhua Tang
Keyword(s):  
Navigation System ◽  
Position Estimation ◽  
Variational Bayesian ◽  
Block Algorithm ◽  
Matrix Block

Experimental research of indoor navigation system based on broadcast signals

2020 ◽  
Vol 49 (5) ◽  
pp. 49-57
Author(s):  
A. V. Ksendzuk ◽  
E. A. Surmin ◽  
V. V. Kachesov ◽  
S. O. Zhdanov ◽  
K. S. Shakhalov
Keyword(s):  
Navigation System ◽  
Open Space ◽  
Position Estimation ◽  
Indoor Navigation ◽  
Estimation Accuracy ◽  
Satellite Systems ◽  
Indoor Navigation System ◽  
Point To Point ◽  
Navigation Signals ◽  
Navigation Equipment

Results of an experimental study of a local navigation system based on the processing signals from broadcast sources presented. The results of the development of processing algorithms for point-to-point coordinates estimation of the object are presented. The results of the development of algorithms for trajectories estimation are presented. In performed simulation the possibility of obtaining submeter position estimation accuracy in the proposed system is shown. Development results of the navigation module demonstrator are presented. The results of experimental work in difficult navigation conditions, in the presence of shading, reflections and other factors, are presented. It is shown that the developed navigation module allows in the open space near buildings which partially obscuring the satellite systems signals to obtain accuracy higher than the GNSS navigation equipment. In indoor environment in the absence of satellite navigation signals, the developed module shows positioning accuracy not worse than 1.5 meters and provides a measurement rate 1 Hz and better.

scholarly journals Estimation of UAV Position with Use of Smoothing Algorithms

2017 ◽  
Vol 24 (1) ◽  
pp. 127-142 ◽  
Author(s):  
Piotr Kaniewski ◽  
Rafał Gil ◽  
Stanisław Konatowski
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Position Estimation ◽  
Fixed Interval ◽  
Smoothing Algorithm ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Gnss Receiver ◽  
On Line

Abstract The paper presents methods of on-line and off-line estimation of UAV position on the basis of measurements from its integrated navigation system. The navigation system installed on board UAV contains an INS and a GNSS receiver. The UAV position, as well as its velocity and orientation are estimated with the use of smoothing algorithms. For off-line estimation, a fixed-interval smoothing algorithm has been applied. On-line estimation has been accomplished with the use of a fixed-lag smoothing algorithm. The paper includes chosen results of simulations demonstrating improvements of accuracy of UAV position estimation with the use of smoothing algorithms in comparison with the use of a Kalman filter.

Development and Performance Validation of a Navigation System for an Underwater Vehicle

2016 ◽  
Vol 69 (5) ◽  
pp. 1097-1113 ◽  
Author(s):  
R. Ramesh ◽  
V. Bala Naga Jyothi ◽  
N. Vedachalam ◽  
G.A. Ramadass ◽  
M.A. Atmanand
Keyword(s):  
Shallow Water ◽  
Navigation System ◽  
Estimation Algorithm ◽  
Initial Position ◽  
Position Estimation ◽  
Doppler Velocity ◽  
Unmanned Underwater Vehicles ◽  
Labview Software ◽  
Position Data ◽  
And Performance

Underwater position data is a key requirement for the navigation and control of unmanned underwater vehicles. The proposed navigation scheme can be used in any vessel or boat for any shallow water vehicle. This paper presents the position estimation algorithm developed for shallow water Remotely Operated Vehicles (ROVs) using attitude data and Doppler Velocity Log data with the initial position from the Global Positioning System (GPS). The navigational sensors are identified using the in-house developed simulation tool in MATLAB, based on the requirement of a position accuracy of less than 5%. The navigation system is built using the identified sensors, Kalman filter and navigation algorithm, developed in LabVIEW software. The developed system is tested and validated for position estimation, with an emulator consisting of a GPS-aided fibre optic gyro-based inertial navigation system as a reference, and it is found that the developed navigation system has a position error of less than 5%.

Velocity Measurement using the Fdoa Method in Ground-Based Radio Navigation System

2014 ◽  
Vol 21 (2) ◽  
pp. 363-376 ◽  
Author(s):  
Jarosław Sadowski
Keyword(s):  
Navigation System ◽  
Velocity Measurement ◽  
Moving Objects ◽  
Radio Networks ◽  
Position Estimation ◽  
Velocity Measurements ◽  
Radio Navigation ◽  
Wave Measurements ◽  
Radio Navigation System ◽  
Full Synchronization

Abstract Velocity is one of the main navigation parameters of moving objects. However some systems of position estimation using radio wave measurements cannot provide velocity data due to limitation of their performance. In this paper a velocity measurement method for the DS-CDMA radio navigation system is proposed, which does not require full synchronization of reference stations carrier frequencies. The article presents basics of FDOA (frequency difference of arrival) velocity measurements together with application of this method to an experimental radio navigation system called AEGIR and with some suggestions about the possibility to implement such FDOA measurements in other kinds of asynchronous DS-CDMA radio networks. The main part of this paper present results of performance evaluation of the proposed method, based on laboratory measurements

Position Estimation by Wearable Walking Navigation System for Visually Impaired with Sensor Fusion

2011 ◽  
Vol 131 (4) ◽  
pp. 490-496 ◽  
Author(s):  
Hiromi Watanabe ◽  
Yoshihiko Yamamoto ◽  
Tsutomu Tanzawa ◽  
Shinji Kotani
Keyword(s):  
Sensor Fusion ◽  
Navigation System ◽  
Visually Impaired ◽  
Position Estimation
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