localization of a moving marine target by using simultaneously GEO satellites and kalman filter

Document Type : Original Article

Authors

1 Imam Hossein (as) University

2 Faculty of Electrical, Electronic Warfare and cyber, Imam Hossein University, Tehran, Iran

Abstract

Localization has many applications and there are different methods to do it. This research has focused on the Geolocationing of the moving marine target with emphasis on the simultaneous use of GEO satellites and the Kalman filter. For Geolocationing using GEO satellites, the technique of simultaneous use of TDOA and FDOA was used. Due to the presence of motion and non-zero velocity for the target, the relationships used in the localization equations by GEO satellite lose their effectiveness and the number of unknowns becomes more than the number of equations. For this purpose, we use the Kalman filter to reduce these unknowns by using the predicted speed given by the Kalman filter and to be able to do the localization by the GEO satellite equations. Additionally, the Kalman filter uses the position obtained by the GEO equations and makes them smoother. According to the findings of this research, the Kalman filter was able to accurately estimate the location and speed of the moving sea target.

Keywords


[1]
K. C. Ho and Y. T. Chan, "Geolocation of a known altitude object from TDOA and FDOA measurements," IEEE transactions on aerospace and electronic systems, vol. 33, no. 3, pp. 770-783, 1997.
[2]
D. Haworth, N. G. Smith, R. Bardelli and T. Clement, "Interference localization for EUTELSAT satellites-the first european transmitter location system," International Journal of satellite communications, vol. 15, no. 4, pp. 155-183, 1997.
[3]
H. Yan, J. K. Cao and L. Chen, "Study on location accuracy of Dual-Satellite Geolocation system," in IEEE 10th International Conference on Signal Processing Proceedings, IEEE, 2010.
[4]
C. Liu, L. Yang and L. Mihaylova, "Dual-satellite source geolocation with time and frequency offsets and satellite location errors," in 2017 20th International Conference on Information Fusion (Fusion), IEEE, 2017.
[5]
R. Bardelli, D. Haworth and N. Smith, "Interference Localization for The Eutelsat Satellite System," IEEE, vol. 3, pp. 1641-1651, 1995.