Moving target positioning algorithm based on multidimensional scaling analysis from TDOA and FDOA with sensor uncertainties

Abstract

The problem of moving target localization from range and velocity difference measurements has attracted considerable attention in recent years. In this article, a novel weighted multidimensional scaling (MDS) algorithm is proposed to estimate the position and velocity of a moving target by utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements with sensor position and velocity errors. The proposed estimator is based on the optimization of a cost function related to the scalar product matrix in classical MDS. The estimator is accurate and closed form. The algorithm has a small mean square error compared with the 2-step weighted least squares (LS) algorithm in a moderate and high noise power level.

Keywords:

• Positioning
• multidimensional scaling
• time/frequency difference of arrivals
• sensor uncertainties
• CRLB

Reviewing Editor:

• Ai Qingsong, Wuhan University of Technology, CHINA

Subjects:

• Technology
• Engineering & Technology
• Electrical & Electronic Engineering
• Communications & Information Processing
• Communication Networks & Systems
• Electromagnetics & Communication
• Telecommunication

Disclosure statement

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Funding

The authors declare that no funds, grants or other support were received during the preparation of this manuscript.

Notes on contributors

Hesham Ibrahim Ahmed

Hesham Ibrahim Ahmed, Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Khartoum D.Eng. 2017, M. Eng. 2013 in Information and Communication Engineering, School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu City, Sichuan, China. BSc in Electrical and Computer Engineering 2009 faculty of Engineering, Karary University, Omdurman, Sudan. Current interests include Signal and Information processing, Radar, and communication systems.