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Deploying multiple unmanned aerial vehicles (UAVs) to locate asignal-emitting source covers a wide range of military and civilianapplications like rescue and target tracking. It is well known that theUAVs-source (sensors-target) geometry, namely geometric configuration,significantly affects the final localization accuracy. This paper focuses onthe geometric configuration optimization for received signal strengthdifference (RSSD)-based passive source localization by drone swarm. Differentfrom prior works, this paper considers a general measuring condition where thespread angle of drone swarm centered on the source is constrained. Subject tothis constraint, a geometric configuration optimization problem with the aim ofmaximizing the determinant of Fisher information matrix (FIM) is formulated.After transforming this problem using matrix theory, an alternating directionmethod of multipliers (ADMM)-based optimization framework is proposed. To solvethe subproblems in this framework, two global optimal solutions based on theVon Neumann matrix trace inequality theorem and majorize-minimize (MM)algorithm are proposed respectively. Finally, the effectiveness as well as thepracticality of the proposed ADMM-based optimization algorithm are demonstratedby extensive simulations.

An ADMM-Based Geometric Configuration Optimization in RSSD-Based Source Localization By UAVs with Spread Angle Constraint