Abstract
When an unknown target emits a radio signal, its position can be localized by a network of sensors (or radar receivers) using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem. In addition, we propose a robust target localization method based on semidefinite programming when the sensor locations are not exactly known. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
