Title: An inertial and global positioning system based algorithm for ownship navigation

Authors: Ihsan Ullah; Bizzat Hussain Zaidi; Shafaq Nisar; Uzair Khan; Mohsin Ali; Sajjad Manzoor

Addresses: Department of Electrical and Computer Engineering, CUI, Abbottabad Campus, Abbottabad, 22060, Pakistan ' Department of Electrical Engineering, DHA Suffa University, Karachi, 75500, Pakistan ' Department of Electrical and Computer Engineering, CUI, Abbottabad Campus, Abbottabad 22060, Pakistan ' Department of Electrical and Computer Engineering, CUI, Abbottabad Campus, Abbottabad 22060, Pakistan ' Department of Computer Engineering, Khwaja Fareed University of Engineering and Information Technology (KFUEIT), Rahim Yar Khan, 64200, Pakistan ' Department of Electrical Engineering, Mirpur University of Science and Technology (MUST), Mirpur, 10250, AJK, Pakistan

Abstract: In this paper a fusion algorithm for global positioning systems (GPS) and inertial navigation system (INS), using inertial measurement unit (IMU), is proposed for ground vehicle trajectory estimation during a GPS outage. As a standalone system an INS has its limitations and an error growth as a result of bias and drift inherent to this sensor restricts its application. A GPS can be used for vehicle navigation flawlessly, however the navigation performance may suffer due to intentional or unintentional GPS signal outage. The proposed GPS-INS fusion algorithm is able to handle any GPS blackout, restrict the INS error development and estimate a precise ownship position while utilising information from two route frameworks, i.e., the GPS and the INS. The proposed GPS-INS based matched state cascaded fusion (MSCF) algorithm, is validated by finding a decrease in it's root mean squared error (RMSE) using experiments and simulations.

Keywords: sensor fusion; GPS; global positioning systems; INS; inertial navigation system; IMU; inertial measurement unit; MSCF; matched state cascaded fusion; RMSE; root mean square error.

DOI: 10.1504/IJSNET.2021.119487

International Journal of Sensor Networks, 2021 Vol.37 No.4, pp.209 - 218

Received: 19 Feb 2021
Accepted: 20 Feb 2021

Published online: 07 Dec 2021 *

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