Abstract
Passive source localization via multiple unmanned aerial vehicles (UAVs) is a key technology for the practical application of military reconnaissance. Previous studies primarily focused on the localization of a single source. This study explores the multi-source passive localization problem using time difference of arrival (TDOA) measurements. We formulate the localization problem as a constrained weighted least squares problem. The formulation is an indefinite quadratically constrained quadratic programming problem, which is non-convex and NP-hard. To obtain approximate programming with linear constraints, an iterative constrained weighted least squares (CWLS) algorithm is proposed to perform a linearization procedure on the quadratic equality constraints. Theoretical analysis reveals that the proposed algorithm, if converges, can lead to a global optimal solution of the formulated problem. The results of the Monte Carlo experiment indicate that the proposed algorithm quickly converges in most situations and offers better localization accuracy compared with the previous two-step weighted least squares method.
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.
