Robust target localization in moving radar platform through semidefinite relaxation

• Published in: 2009 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 2209 - 2212
• Main Authors: Yimin Zhang, Kehu Yang, Amin, M.G.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2009
• Subjects: Least squares approximation; Maximum likelihood estimation; Military communication; optimization methods; position estimation; Position measurement; Radar applications; Radar measurements; Radar signal processing; Robustness; semidefinite relaxation; Sensor systems and applications; Surveillance; Synthetic aperture radar
• ISBN: 9781424423538; 1424423538
• ISSN: 1520-6149
• DOI: 10.1109/ICASSP.2009.4960057

Accurate target localization is an important task in various commercial and military applications. One way to achieve this goal is to use the time-of-arrival (TOA) or time-delay-of-arrival (TDOA) information observed at multiple distributed sensors. On the other hand, there is a great need to use moving sensors to form a radar platform with synthetic apertures. In this paper, we consider the problem of target localization based on the range information estimated from two-way time-of-flight (TW-TOF) at multiple synthetic array locations, where the position of these synthetic array locations is subject to certain random errors. The nonconvex estimation problem is approximated by a convex optimization problem using the semidefinite relaxation (SDR) approach. Simulation results show that the proposed estimator provides mean square position error performance close to the Cramer-Rao lower bound.